Frontiers & Opportunities前沿与机遇
A daily reading desk for research, engineering, industry and academic opportunities.每天花一点时间，发现值得研究、值得借鉴、值得动手验证的新进展。
北京时间 2026-10-20 09:06 更新 · 最新原文 2026-10-19 · 请核对日期
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定时计划：北京时间每天早间更新；实际以最后成功抓取时间为准。部分来源失败时保留历史内容。
当前抓取：部分来源失败；成功 32 个请求，失败 2 个请求。成功取得内容不代表结论已核实。
Horizon：采集 success；模型解读部分失败。本次已报告用量 11489 tokens。
模型路由：openai / minimax/minimax-m3.1-flash:free → openai / xingchen-agi/xing4.0-29b-a4b:free → openai / nvidia/nemotron-3.5-super-vl:free → deepseek / deepseek-flash。GitHub Actions 云端执行，不依赖个人电脑；免费目录 17 个候选，状态 credential_configured。免费模型受平台额度及可用性限制。
本次实际调用：minimax/minimax-m3.1-flash:free · 成功；minimax/minimax-m3.1-flash:free · 成功；minimax/minimax-m3.1-flash:free · 成功；minimax/minimax-m3.1-flash:free · 失败，已尝试后续路线；xingchen-agi/xing4.0-29b-a4b:free · 失败，已尝试后续路线；nvidia/nemotron-3.5-super-vl:free · 失败，已尝试后续路线；deepseek-flash · 失败，已尝试后续路线。
本期精选
10 条阅读线索 · 研究、工具与跨领域观察
通过多教师蒸馏框架学习多个互补的语音表示Learning Speech Attribute Representations via Multi-Teacher Distillation
文章提出了一种多属性多教师蒸馏框架，用于同时学习多个互补的语音表示。Recent post-training approaches have shown that self-supervised speech encoders can be adapted to learn a single utterance-level speech attribute through knowledge distillation. In this work, we investigate whether a single speech encoder can simultaneously preserve multiple complementary utterance-level speech representations. We propose a multi-attribute multi-teacher distillation framework that learns semantic, speaker,...
预印本摘要 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、具身与端侧产品、科研与开发提效
原文要点 文章提出了一种多属性多教师蒸馏框架，用于同时学习多个互补的语音表示。
研究关联 该研究与语音编码器的改进和知识蒸馏技术有关，特别是在多教师学习框架下的应用。这与语音识别和语音处理领域的研究方向紧密相关。
行动建议 建议阅读相关文献，了解多教师蒸馏框架在语音编码器中的应用情况。
证据与限制 证据层级较低，仅基于摘要信息。缺少具体实验细节、代码和数据集的可得性。可能失效条件包括实验设计的局限性和数据集的代表性问题。
RISHAB-999/TherapiquesRISHAB-999/Therapiques
A modern full-stack mental health platform featuring doctor appointment booking, real-time WebRTC video consultations, live chat, interactive psychology bookstore & library, AI assistant, and Razorpay/Stripe payments. Recent GitHub repository activity related to AI psychology mental health, updated within the latest 30-day window. Primary language: JavaScript.A modern full-stack mental health platform featuring doctor appointment booking, real-time WebRTC video consultations, live chat, interactive psychology bookstore & library, AI assistant, and Razorpay/Stripe payments. Recent GitHub repository activity related to AI psychology mental health, updated within the latest 30-day window. Primary language: JavaScript.
仓库公开说明 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、科研与开发提效、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Timestral: Mistral's time-series foundation modelsTimestral: Mistral's time-series foundation models
--- Top Comments --- [yaoke259]: ChatGPT became massive because of it's generalisability without needing training a new model for every domain and for its zero-shot learning inference/learning capabilities. If this model can be scaled or easily fine-tuned, it can have huge implications on forecasting in domains where custom models are too hard or too expensive! I am somewhat sceptical and wonder if the big quant firms already have versions of this internally or if not, why no one has achieved these kinds of results... [joefourier]: My field is primarily audio/vision ML so I don't have any particular domain expertise, but I don't get how you can lump all "time-series" together in one big bucket. My naive understanding is that the way to impr--- Top Comments --- [yaoke259]: ChatGPT became massive because of it's generalisability without needing training a new model for every domain and for its zero-shot learning inference/learning capabilities. If this model can be scaled or easily fine-tuned, it can have huge implications on forecasting in domains where custom models are too hard or too expensive! I am somewhat sceptical and wonder if the big quant firms already have versions of this internally or if not, why no one has achieved these kinds of results... [joefourier]: My field is primarily audio/vision ML so I don't have any particular domain expertise, but I don't get how you can lump all "time-series" together in one big bucket. My naive understanding is that the way to impr
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、科研与开发提效、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
预印本摘要：提示演化在压力与情绪预测中的策略识别Identifying Effective Strategies in Prompt Evolution for Stress and Emotion Prediction
该预印本摘要讨论基于大语言模型进行压力与情绪预测时的提示演化策略。摘要称，研究比较了社交媒体场景中的六种方法，并指出仅依赖准确率可能掩盖假阳性；提示修改在不同模型和任务上的收益不一致，且这些收益与策略组合、指令变化之间的关系尚不明确。提供的摘要内容在“on social media...”处截断，未给出具体实验结果、作者信息或实验细节。Early stress detection and risk prediction are crucial for timely mental health assessment and support. While large language models have recently shown promise for social media stress prediction, relying on accuracy can obscure false positives. Also, prompt revisions yield inconsistent gains across models and tasks, with unclear links to strategy combinations and instruction changes. By comparing six methods on social media...
预印本摘要 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、跨学科与产业转化
原文要点 该预印本摘要讨论基于大语言模型进行压力与情绪预测时的提示演化策略。摘要称，研究比较了社交媒体场景中的六种方法，并指出仅依赖准确率可能掩盖假阳性；提示修改在不同模型和任务上的收益不一致，且这些收益与策略组合、指令变化之间的关系尚不明确。提供的摘要内容在“on social media...”处截断，未给出具体实验结果、作者信息或实验细节。
研究关联 该条目直接关联情感计算、基于社交媒体的心理健康与压力预测、大语言模型提示工程，以及模型评估方法。其具体价值在于提出一个可检验的评估问题：提示演化带来的准确率变化，可能掩盖假阳性风险；不同模型和任务上的提示收益也可能不稳定。这适合作为提示策略比较与心理健康预测评估设计的阅读线索，但目前只是预印本摘要层面的问题陈述，不是已验证结论。
行动建议 建议：获取全文并进行一次结构化阅读，重点核对研究问题、六种方法的实验范围、基线是否在同模型同数据同预算下比较，以及代码和数据是否可得；在完成核对前，不引用摘要中的结论。
证据与限制 证据层级仅为预印本摘要，且所给内容截断；没有全文、具体实验指标、数据集信息、基线设置、代码或数据可得性说明，作者信息也未标明，因此无法核对研究问题是否被完整回答、实验范围是否充分、基线比较是否公平，以及结果能否复现。若全文显示基线不公平、任务或数据范围过窄、只报告准确率而未处理假阳性，或提示收益无法跨模型和任务稳定出现，则摘要中的相关表述可能失效。不能把该预印本摘要的表述写成定论。
多模态大语言模型在卡通电影中的社会和情感理解Brain-Aligned Multimodal LLMs for Social and Emotional Understanding of Cartoon Movies
文章研究了多模态大语言模型（MLLMs）在卡通电影中的社会和情感内容注释，并与人类的理论思维（ToM）和情感价值进行了比较。研究通过三个短篇卡通电影评估了扩散模型和自回归模型的性能。Multimodal large language models (MLLMs) offer scalable annotations of social and affective content, but their temporal agreement with human judgments and neural predictive value require further evaluation. We compared diffusion-based and autoregressive MLLMs with continuous human Theory of Mind (ToM) and affective valence ratings across three short cartoon movies. Behavioral analyses assessed temporally aligned Pearson...
预印本摘要 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、科研与开发提效
原文要点 文章研究了多模态大语言模型（MLLMs）在卡通电影中的社会和情感内容注释，并与人类的理论思维（ToM）和情感价值进行了比较。研究通过三个短篇卡通电影评估了扩散模型和自回归模型的性能。
研究关联 该研究与情感计算、多模态感知、心理计算和人因工程等公开研究方向直接相关，探讨了多模态大语言模型在社会和情感理解中的应用。
行动建议 建议阅读相关文献，了解多模态大语言模型在社会和情感理解中的应用现状和挑战。
证据与限制 证据层级较低，仅基于摘要信息，缺少具体实验细节和数据。可能失效条件包括模型性能的局限性、数据集的代表性不足以及评估方法的局限性。
Cross-Dimension and Cross-Modality Relational Tensor Representation Learning for Multimodal Health Data ModelingCross-Dimension and Cross-Modality Relational Tensor Representation Learning for Multimodal Health Data Modeling
Multimodal health data integrate information from heterogeneous clinical sources, creating substantial opportunities for data-driven decision support. Realizing these opportunities, however, requires effectively modeling complex dependencies that arise both within individual modalities and across modalities. This paper proposes Relational Tensor Representation (RTR), a unified framework that jointly learns dimension-specific...Multimodal health data integrate information from heterogeneous clinical sources, creating substantial opportunities for data-driven decision support. Realizing these opportunities, however, requires effectively modeling complex dependencies that arise both within individual modalities and across modalities. This paper proposes Relational Tensor Representation (RTR), a unified framework that jointly learns dimension-specific...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Advancing coding in low‑resource programming languagesAdvancing coding in low‑resource programming languages
Learn how OpenAI is improving ChatGPT across low-resource programming languages, with new evaluations for software engineering, SQLite, and COBOL migration.Learn how OpenAI is improving ChatGPT across low-resource programming languages, with new evaluations for software engineering, SQLite, and COBOL migration.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 科研复现、开发工具与资源管理。匹配：科研与开发提效
阅读建议 先核对许可、依赖与复现条件；若适用，用隔离的小任务验证时间和资源收益。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Itaú 使用 AI 增强客户和员工互动How Itaú is building generative AI for its entire customer base
Itaú 正在使用 AI 通过对话界面和治理平台来增强客户和员工的互动，但文章没有提供具体的实施细节。With ia.i, a conversational interface, and the IARA governance platform, Itaú is applying its AI First strategy to customers and employees — in one of Brazil’s most regulated sectors.
公开来源摘录 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 跨学科方法与产品落地。匹配：跨学科与产业转化
原文要点 Itaú 正在使用 AI 通过对话界面和治理平台来增强客户和员工的互动，但文章没有提供具体的实施细节。
研究关联 Itaú 的 AI 战略在巴西银行业这样一个高度监管的领域中应用，与 AI 治理和对话式 AI 的研究方向密切相关。
行动建议 建议阅读更多关于 Itaú 的 AI 治理平台 IARA 和对话界面 ia.i 的具体技术细节。
证据与限制 文章缺乏具体的实施细节和技术方法，证据层级较低，无法提供详细的验证依据。可能失效条件包括技术细节的缺失和监管环境的变化。
Alternatives to animal testing are finally taking offAlternatives to animal testing are finally taking off
--- Top Comments --- [willmeyers]: As slow as it may be to adopt, it's a welcome change to how people should do research. Why induce suffering on an animal when the potential for failure and or miscalculation is so high? It seems from the article a model/chip can be more insightful on how something will affect humans. [Spacecosmonaut]: The dirty little secret of human organoid models is that they are grown in a matrix (e.g. Matrigel) that is derived from a tumor that secretes this matrix, which is grown in a mouse host. The mouse of course is "sacrificed" to harvest this matrix. [PaulHoule]: Whenever i go all the way to the east coast I run into these guys https://en.wikipedia.org/wiki/Horseshoe_crab And because of the unusual nature of the--- Top Comments --- [willmeyers]: As slow as it may be to adopt, it's a welcome change to how people should do research. Why induce suffering on an animal when the potential for failure and or miscalculation is so high? It seems from the article a model/chip can be more insightful on how something will affect humans. [Spacecosmonaut]: The dirty little secret of human organoid models is that they are grown in a matrix (e.g. Matrigel) that is derived from a tumor that secretes this matrix, which is grown in a mouse host. The mouse of course is "sacrificed" to harvest this matrix. [PaulHoule]: Whenever i go all the way to the east coast I run into these guys https://en.wikipedia.org/wiki/Horseshoe_crab And because of the unusual nature of the
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Faraday Future和FFR联合发布FF Nova和FF Nova MiniFaraday Future and FFR Jointly Launch FF Nova, First Embodied AI Humanoid Robot Priced Below $2,500 in U.S., FF Nova Mini, Physical AI Spark Program Curriculum, Nova Reinforcement Learning Developer Program and Developer Community Recruitme - Rutland Herald
Faraday Future和FFR联合发布了价格低于2500美元的FF Nova和FF Nova Mini，并推出了相关的开发者计划。Faraday Future and FFR Jointly Launch FF Nova, First Embodied AI Humanoid Robot Priced Below $2,500 in U.S., FF Nova Mini, Physical AI Spark Program Curriculum, Nova Reinforcement Learning Developer Program and Developer Community Recruitme Rutland Herald
公开来源摘录 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品、科研与开发提效、跨学科与产业转化
原文要点 Faraday Future和FFR联合发布了价格低于2500美元的FF Nova和FF Nova Mini，并推出了相关的开发者计划。
研究关联 该发布与人工智能和机器人技术领域的研究方向密切相关，特别是涉及情感计算、多模态感知和强化学习等领域的应用。
行动建议 建议关注FF Nova和FF Nova Mini的技术细节和开发者计划的具体内容，以评估其在实际应用中的潜力。
证据与限制 文章缺乏具体的技术细节和证据，难以评估FF Nova和FF Nova Mini在情感计算、多模态感知等领域的实际贡献。此外，价格低于2500美元的机器人在市场上的竞争力和实际应用效果尚需验证。
研究、工具与产业资料库
按栏目和方向收敛阅读范围；保留原文日期、出处和证据边界。
通过多教师蒸馏框架学习多个互补的语音表示Learning Speech Attribute Representations via Multi-Teacher Distillation
文章提出了一种多属性多教师蒸馏框架，用于同时学习多个互补的语音表示。Recent post-training approaches have shown that self-supervised speech encoders can be adapted to learn a single utterance-level speech attribute through knowledge distillation. In this work, we investigate whether a single speech encoder can simultaneously preserve multiple complementary utterance-level speech representations. We propose a multi-attribute multi-teacher distillation framework that learns semantic, speaker,...
预印本摘要 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、具身与端侧产品、科研与开发提效
原文要点 文章提出了一种多属性多教师蒸馏框架，用于同时学习多个互补的语音表示。
研究关联 该研究与语音编码器的改进和知识蒸馏技术有关，特别是在多教师学习框架下的应用。这与语音识别和语音处理领域的研究方向紧密相关。
行动建议 建议阅读相关文献，了解多教师蒸馏框架在语音编码器中的应用情况。
证据与限制 证据层级较低，仅基于摘要信息。缺少具体实验细节、代码和数据集的可得性。可能失效条件包括实验设计的局限性和数据集的代表性问题。
RISHAB-999/TherapiquesRISHAB-999/Therapiques
A modern full-stack mental health platform featuring doctor appointment booking, real-time WebRTC video consultations, live chat, interactive psychology bookstore & library, AI assistant, and Razorpay/Stripe payments. Recent GitHub repository activity related to AI psychology mental health, updated within the latest 30-day window. Primary language: JavaScript.A modern full-stack mental health platform featuring doctor appointment booking, real-time WebRTC video consultations, live chat, interactive psychology bookstore & library, AI assistant, and Razorpay/Stripe payments. Recent GitHub repository activity related to AI psychology mental health, updated within the latest 30-day window. Primary language: JavaScript.
仓库公开说明 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、科研与开发提效、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Timestral: Mistral's time-series foundation modelsTimestral: Mistral's time-series foundation models
--- Top Comments --- [yaoke259]: ChatGPT became massive because of it's generalisability without needing training a new model for every domain and for its zero-shot learning inference/learning capabilities. If this model can be scaled or easily fine-tuned, it can have huge implications on forecasting in domains where custom models are too hard or too expensive! I am somewhat sceptical and wonder if the big quant firms already have versions of this internally or if not, why no one has achieved these kinds of results... [joefourier]: My field is primarily audio/vision ML so I don't have any particular domain expertise, but I don't get how you can lump all "time-series" together in one big bucket. My naive understanding is that the way to impr--- Top Comments --- [yaoke259]: ChatGPT became massive because of it's generalisability without needing training a new model for every domain and for its zero-shot learning inference/learning capabilities. If this model can be scaled or easily fine-tuned, it can have huge implications on forecasting in domains where custom models are too hard or too expensive! I am somewhat sceptical and wonder if the big quant firms already have versions of this internally or if not, why no one has achieved these kinds of results... [joefourier]: My field is primarily audio/vision ML so I don't have any particular domain expertise, but I don't get how you can lump all "time-series" together in one big bucket. My naive understanding is that the way to impr
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、科研与开发提效、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
预印本摘要：提示演化在压力与情绪预测中的策略识别Identifying Effective Strategies in Prompt Evolution for Stress and Emotion Prediction
该预印本摘要讨论基于大语言模型进行压力与情绪预测时的提示演化策略。摘要称，研究比较了社交媒体场景中的六种方法，并指出仅依赖准确率可能掩盖假阳性；提示修改在不同模型和任务上的收益不一致，且这些收益与策略组合、指令变化之间的关系尚不明确。提供的摘要内容在“on social media...”处截断，未给出具体实验结果、作者信息或实验细节。Early stress detection and risk prediction are crucial for timely mental health assessment and support. While large language models have recently shown promise for social media stress prediction, relying on accuracy can obscure false positives. Also, prompt revisions yield inconsistent gains across models and tasks, with unclear links to strategy combinations and instruction changes. By comparing six methods on social media...
预印本摘要 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、跨学科与产业转化
原文要点 该预印本摘要讨论基于大语言模型进行压力与情绪预测时的提示演化策略。摘要称，研究比较了社交媒体场景中的六种方法，并指出仅依赖准确率可能掩盖假阳性；提示修改在不同模型和任务上的收益不一致，且这些收益与策略组合、指令变化之间的关系尚不明确。提供的摘要内容在“on social media...”处截断，未给出具体实验结果、作者信息或实验细节。
研究关联 该条目直接关联情感计算、基于社交媒体的心理健康与压力预测、大语言模型提示工程，以及模型评估方法。其具体价值在于提出一个可检验的评估问题：提示演化带来的准确率变化，可能掩盖假阳性风险；不同模型和任务上的提示收益也可能不稳定。这适合作为提示策略比较与心理健康预测评估设计的阅读线索，但目前只是预印本摘要层面的问题陈述，不是已验证结论。
行动建议 建议：获取全文并进行一次结构化阅读，重点核对研究问题、六种方法的实验范围、基线是否在同模型同数据同预算下比较，以及代码和数据是否可得；在完成核对前，不引用摘要中的结论。
证据与限制 证据层级仅为预印本摘要，且所给内容截断；没有全文、具体实验指标、数据集信息、基线设置、代码或数据可得性说明，作者信息也未标明，因此无法核对研究问题是否被完整回答、实验范围是否充分、基线比较是否公平，以及结果能否复现。若全文显示基线不公平、任务或数据范围过窄、只报告准确率而未处理假阳性，或提示收益无法跨模型和任务稳定出现，则摘要中的相关表述可能失效。不能把该预印本摘要的表述写成定论。
多模态大语言模型在卡通电影中的社会和情感理解Brain-Aligned Multimodal LLMs for Social and Emotional Understanding of Cartoon Movies
文章研究了多模态大语言模型（MLLMs）在卡通电影中的社会和情感内容注释，并与人类的理论思维（ToM）和情感价值进行了比较。研究通过三个短篇卡通电影评估了扩散模型和自回归模型的性能。Multimodal large language models (MLLMs) offer scalable annotations of social and affective content, but their temporal agreement with human judgments and neural predictive value require further evaluation. We compared diffusion-based and autoregressive MLLMs with continuous human Theory of Mind (ToM) and affective valence ratings across three short cartoon movies. Behavioral analyses assessed temporally aligned Pearson...
预印本摘要 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、科研与开发提效
原文要点 文章研究了多模态大语言模型（MLLMs）在卡通电影中的社会和情感内容注释，并与人类的理论思维（ToM）和情感价值进行了比较。研究通过三个短篇卡通电影评估了扩散模型和自回归模型的性能。
研究关联 该研究与情感计算、多模态感知、心理计算和人因工程等公开研究方向直接相关，探讨了多模态大语言模型在社会和情感理解中的应用。
行动建议 建议阅读相关文献，了解多模态大语言模型在社会和情感理解中的应用现状和挑战。
证据与限制 证据层级较低，仅基于摘要信息，缺少具体实验细节和数据。可能失效条件包括模型性能的局限性、数据集的代表性不足以及评估方法的局限性。
MC-TRCM: Observation-Aware Recursive Fusion for Incomplete Mobile and Wearable Mental-Health Feature ViewsMC-TRCM: Observation-Aware Recursive Fusion for Incomplete Mobile and Wearable Mental-Health Feature Views
Public mobile and wearable mental-health datasets often provide summarized feature tables rather than synchronized raw sensor streams. In these releases, each anchor corresponds to a survey or label time and may combine phone or wearable summaries, prior symptom scores, demographics, clinical variables, and source-availability indicators. We propose the Modality-Conditioned Temporal Recursive Context Model (MC-TRCM), which...Public mobile and wearable mental-health datasets often provide summarized feature tables rather than synchronized raw sensor streams. In these releases, each anchor corresponds to a survey or label time and may combine phone or wearable summaries, prior symptom scores, demographics, clinical variables, and source-availability indicators. We propose the Modality-Conditioned Temporal Recursive Context Model (MC-TRCM), which...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、具身与端侧产品、科研与开发提效
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
PsyEvo: A Personalized Counseling Agent That Self-Evolves at Test TimePsyEvo: A Personalized Counseling Agent That Self-Evolves at Test Time
Mental health disorders affect a substantial proportion of the global population, yet a persistent shortage of trained practitioners leaves the majority without adequate care. Large language model (LLM)-based counselors present a promising direction for delivering scalable conversational psychological support. Offline model training alone leaves limited room to adapt to individual clients or to learn from ongoing therapeutic...Mental health disorders affect a substantial proportion of the global population, yet a persistent shortage of trained practitioners leaves the majority without adequate care. Large language model (LLM)-based counselors present a promising direction for delivering scalable conversational psychological support. Offline model training alone leaves limited room to adapt to individual clients or to learn from ongoing therapeutic...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、智能体与团队能力、科研与开发提效
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
SocialHumanoid: Towards Expressive Humanoid Behavior via One-Step Co-Speech Motion GenerationSocialHumanoid: Towards Expressive Humanoid Behavior via One-Step Co-Speech Motion Generation
Humanoid robots are increasingly expected to serve as embodied social agents that communicate naturally with humans through face-to-face interaction. During such communication, humanoid robots require body behaviors that are synchronized with speech, affectively expressive, and suitable for real-time execution. However, existing co-speech methods are primarily developed for digital humans and lack joint support for affective...Humanoid robots are increasingly expected to serve as embodied social agents that communicate naturally with humans through face-to-face interaction. During such communication, humanoid robots require body behaviors that are synchronized with speech, affectively expressive, and suitable for real-time execution. However, existing co-speech methods are primarily developed for digital humans and lack joint support for affective...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、智能体与团队能力、具身与端侧产品
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
A Procedure for Classifying Attachments and Affective Social Bonds in Human-Robot DyadsA Procedure for Classifying Attachments and Affective Social Bonds in Human-Robot Dyads
Human-robot interaction (HRI) claims that people form attachments and social bonds with artificial agents, yet the terms are often applied without the behavioural and physiological criteria that give them content in their source disciplines. Without this empirical grounding, studies deploy widely divergent methods, frequently producing expansive relational claims that far outstrip their underlying evidence. To address this,...Human-robot interaction (HRI) claims that people form attachments and social bonds with artificial agents, yet the terms are often applied without the behavioural and physiological criteria that give them content in their source disciplines. Without this empirical grounding, studies deploy widely divergent methods, frequently producing expansive relational claims that far outstrip their underlying evidence. To address this,...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、智能体与团队能力
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
OpenRoIS: A Community-Driven Open-Source Middleware Implementing the Robotic Interaction Service (RoIS) Framework for Physical Robots and Virtual AgentsOpenRoIS: A Community-Driven Open-Source Middleware Implementing the Robotic Interaction Service (RoIS) Framework for Physical Robots and Virtual Agents
Service applications for human-robot interaction are commonly written against the hardware-specific interfaces of one platform, so a change of hardware forces a rewrite of the application. The Robotic Interaction Service (RoIS) Framework 2.0, standardized by the Object Management Group (OMG), addresses this fragmentation by defining a platform-independent model in which Service Applications interact with Human-Robot...Service applications for human-robot interaction are commonly written against the hardware-specific interfaces of one platform, so a change of hardware forces a rewrite of the application. The Robotic Interaction Service (RoIS) Framework 2.0, standardized by the Object Management Group (OMG), addresses this fragmentation by defining a platform-independent model in which Service Applications interact with Human-Robot...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、智能体与团队能力、具身与端侧产品
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Cross-Dimension and Cross-Modality Relational Tensor Representation Learning for Multimodal Health Data ModelingCross-Dimension and Cross-Modality Relational Tensor Representation Learning for Multimodal Health Data Modeling
Multimodal health data integrate information from heterogeneous clinical sources, creating substantial opportunities for data-driven decision support. Realizing these opportunities, however, requires effectively modeling complex dependencies that arise both within individual modalities and across modalities. This paper proposes Relational Tensor Representation (RTR), a unified framework that jointly learns dimension-specific...Multimodal health data integrate information from heterogeneous clinical sources, creating substantial opportunities for data-driven decision support. Realizing these opportunities, however, requires effectively modeling complex dependencies that arise both within individual modalities and across modalities. This paper proposes Relational Tensor Representation (RTR), a unified framework that jointly learns dimension-specific...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Faraday Future和FFR联合发布FF Nova和FF Nova MiniFaraday Future and FFR Jointly Launch FF Nova, First Embodied AI Humanoid Robot Priced Below $2,500 in U.S., FF Nova Mini, Physical AI Spark Program Curriculum, Nova Reinforcement Learning Developer Program and Developer Community Recruitme - Rutland Herald
Faraday Future和FFR联合发布了价格低于2500美元的FF Nova和FF Nova Mini，并推出了相关的开发者计划。Faraday Future and FFR Jointly Launch FF Nova, First Embodied AI Humanoid Robot Priced Below $2,500 in U.S., FF Nova Mini, Physical AI Spark Program Curriculum, Nova Reinforcement Learning Developer Program and Developer Community Recruitme Rutland Herald
公开来源摘录 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品、科研与开发提效、跨学科与产业转化
原文要点 Faraday Future和FFR联合发布了价格低于2500美元的FF Nova和FF Nova Mini，并推出了相关的开发者计划。
研究关联 该发布与人工智能和机器人技术领域的研究方向密切相关，特别是涉及情感计算、多模态感知和强化学习等领域的应用。
行动建议 建议关注FF Nova和FF Nova Mini的技术细节和开发者计划的具体内容，以评估其在实际应用中的潜力。
证据与限制 文章缺乏具体的技术细节和证据，难以评估FF Nova和FF Nova Mini在情感计算、多模态感知等领域的实际贡献。此外，价格低于2500美元的机器人在市场上的竞争力和实际应用效果尚需验证。
VocalGrad: 评估音频语言模型中的声学感知VocalGrad: Evaluating Acoustic Perception in Audio Language Models
文章讨论了大型音频语言模型（LALMs）在情感识别等任务中的局限性，特别是在利用声学信息方面。现有基准测试未能明确区分声学感知与其他音频理解任务。Recent large audio language models (LALMs) have extended their capabilities beyond lexical speech understanding to tasks requiring paralinguistic and non-linguistic audio understanding, such as emotion recognition. However, these models still struggle to reliably utilize acoustic information, particularly when it co-occurs with spoken linguistic content. Existing benchmarks do not clearly distinguish acoustic perception from...
预印本摘要 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效
原文要点 文章讨论了大型音频语言模型（LALMs）在情感识别等任务中的局限性，特别是在利用声学信息方面。现有基准测试未能明确区分声学感知与其他音频理解任务。
研究关联 该研究与情感计算和多模态感知领域相关，特别是探讨了音频语言模型在利用声学信息进行情感识别等方面的局限性。
行动建议 建议阅读相关文献，了解当前音频语言模型在情感识别任务中的具体表现和局限性。
证据与限制 文章缺乏具体证据和详细分析，主要停留在泛化宣传层面。证据层级较低，缺少具体实验数据和验证。可能失效条件包括模型更新和新基准测试的出现。
Known Music, Unknown Response: Leakage-Audited Dynamic Arousal Forecasting With Scheduled Future MusicKnown Music, Unknown Response: Leakage-Audited Dynamic Arousal Forecasting With Scheduled Future Music
Dynamic music emotion recognition usually estimates concurrent or lag-aligned labels from audio that has already been observed. We instead forecast the change in consensus arousal when the upcoming music is scheduled but all later affect labels remain hidden. Evaluation holds out complete songs, encodes each eligible 4-s chunk independently, predicts arousal innovation, and compares the correct future with displaced segments...Dynamic music emotion recognition usually estimates concurrent or lag-aligned labels from audio that has already been observed. We instead forecast the change in consensus arousal when the upcoming music is scheduled but all later affect labels remain hidden. Evaluation holds out complete songs, encodes each eligible 4-s chunk independently, predicts arousal innovation, and compares the correct future with displaced segments...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Edge AI for Smart Cities: From Insight to Cognitive ActionEdge AI for Smart Cities: From Insight to Cognitive Action
This white paper explains how edge AI and physical AI help cities move beyond passive monitoring. It shows how urban infrastructure can sense, reason, and act on real-time conditions across public safety, mobility, and infrastructure management. What you will learn about: How the shift from smart cities to cognitive cities depends on infrastructure that...This white paper explains how edge AI and physical AI help cities move beyond passive monitoring. It shows how urban infrastructure can sense, reason, and act on real-time conditions across public safety, mobility, and infrastructure management. What you will learn about: How the shift from smart cities to cognitive cities depends on infrastructure that...
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、具身与端侧产品
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
The Robot I Didn’t Expect to BuildThe Robot I Didn’t Expect to Build
Agility Robotics , the company I cofounded out of my robotics lab at Oregon State University in 2015, has just launched Digit 5 . It’s designed to be the first humanoid robot that can safely and economically do useful work at scale, allowing us to bring tens of thousands of humanoid workers into the real world. Engineered to lift 23-kilogram bins onto high...Agility Robotics , the company I cofounded out of my robotics lab at Oregon State University in 2015, has just launched Digit 5 . It’s designed to be the first humanoid robot that can safely and economically do useful work at scale, allowing us to bring tens of thousands of humanoid workers into the real world. Engineered to lift 23-kilogram bins onto high...
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品、科研与开发提效
阅读建议 核对延迟、硬件条件、功耗和交互任务，再评估能否迁移到现有设备。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Putting Linux on my RTX Spark laptop because I don't have a Microsoft accountPutting Linux on my RTX Spark laptop because I don't have a Microsoft account
--- Top Comments --- [chem83]: Not sure there's a strong use case for one of these $6K laptops yet, considering you can get a mini PC running AMD Ryzen 495 or 395 with 96, 128 and 192 GB of memory for similar amount of money and connect remotely from a cheaper/smaller/more battery-efficient laptop. Microsoft also has this same chip in non-laptop form factor: https://www.microsoft.com/en-us/surface/devices/surface-rtx-... . Coding while flying is often the use case people bring ... [TIPSIO]: Being forced to login to use your own hardware is one issue for sure… but separately everything about Microsoft’s login experience is pure pain. Multiple broken redirects, broken links, buttons that loop, and more just to hit a CAPTCHA AI can solve anywa--- Top Comments --- [chem83]: Not sure there's a strong use case for one of these $6K laptops yet, considering you can get a mini PC running AMD Ryzen 495 or 395 with 96, 128 and 192 GB of memory for similar amount of money and connect remotely from a cheaper/smaller/more battery-efficient laptop. Microsoft also has this same chip in non-laptop form factor: https://www.microsoft.com/en-us/surface/devices/surface-rtx-... . Coding while flying is often the use case people bring ... [TIPSIO]: Being forced to login to use your own hardware is one issue for sure… but separately everything about Microsoft’s login experience is pure pain. Multiple broken redirects, broken links, buttons that loop, and more just to hit a CAPTCHA AI can solve anywa
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力、科研与开发提效
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Alternatives to animal testing are finally taking offAlternatives to animal testing are finally taking off
--- Top Comments --- [willmeyers]: As slow as it may be to adopt, it's a welcome change to how people should do research. Why induce suffering on an animal when the potential for failure and or miscalculation is so high? It seems from the article a model/chip can be more insightful on how something will affect humans. [Spacecosmonaut]: The dirty little secret of human organoid models is that they are grown in a matrix (e.g. Matrigel) that is derived from a tumor that secretes this matrix, which is grown in a mouse host. The mouse of course is "sacrificed" to harvest this matrix. [PaulHoule]: Whenever i go all the way to the east coast I run into these guys https://en.wikipedia.org/wiki/Horseshoe_crab And because of the unusual nature of the--- Top Comments --- [willmeyers]: As slow as it may be to adopt, it's a welcome change to how people should do research. Why induce suffering on an animal when the potential for failure and or miscalculation is so high? It seems from the article a model/chip can be more insightful on how something will affect humans. [Spacecosmonaut]: The dirty little secret of human organoid models is that they are grown in a matrix (e.g. Matrigel) that is derived from a tumor that secretes this matrix, which is grown in a mouse host. The mouse of course is "sacrificed" to harvest this matrix. [PaulHoule]: Whenever i go all the way to the east coast I run into these guys https://en.wikipedia.org/wiki/Horseshoe_crab And because of the unusual nature of the
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Ask HN: How to deal with shipping AI-written code you don't understand?Ask HN: How to deal with shipping AI-written code you don't understand?
I saw this LinkedIn post from a Meta engineer and it resonated with me:https://www.linkedin.com/posts/ali-hamie_im-an-engineer-at-m...> I'm an engineer at Meta and I never felt this uncomfortable doing my job. I'm writing code these days and it all feels like a black box. This new standard of shipping with AI is moving so fast that if we're going to spend our time checking each line of code, it's going to take forever. That means you can end up with systems you've built where you don't truly understand how all the code works. You understand the high level, but not every detail. And maybe this is becoming the new standard. It goes against every instinct of being a software engineer. I'm used to understanding what I'm building. Now I'm tryingI saw this LinkedIn post from a Meta engineer and it resonated with me:https://www.linkedin.com/posts/ali-hamie_im-an-engineer-at-m...> I'm an engineer at Meta and I never felt this uncomfortable doing my job. I'm writing code these days and it all feels like a black box. This new standard of shipping with AI is moving so fast that if we're going to spend our time checking each line of code, it's going to take forever. That means you can end up with systems you've built where you don't truly understand how all the code works. You understand the high level, but not every detail. And maybe this is becoming the new standard. It goes against every instinct of being a software engineer. I'm used to understanding what I'm building. Now I'm trying
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、科研与开发提效
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
ACR-Net: 缓解语义主导问题的对比声学-语义解耦方法ACR-Net: Mitigating Semantic Dominance via Contrastive Acoustic-Semantic Decoupling
文章提出了ACR-Net模型，通过对比声学-语义解耦来缓解语义主导问题，引入了ASPIRE基准和两个评估指标，以解决语音情感识别和音频LLM在跨模态冲突中的文本偏见问题。Speech Emotion Recognition (SER) models and Audio LLMs fail when vocal tone contradicts textual semantics. Extensive training on congruent data engenders a rigid semantic prior, causing "Semantic Dominance", a severe text bias during cross-modal conflicts. We introduce the ASPIRE benchmark of adversarial audio-text pairs across four conflict types, alongside two metrics: Semantic Overconfidence Penalty (SOP) and Latent...
预印本摘要 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效
原文要点 文章提出了ACR-Net模型，通过对比声学-语义解耦来缓解语义主导问题，引入了ASPIRE基准和两个评估指标，以解决语音情感识别和音频LLM在跨模态冲突中的文本偏见问题。
研究关联 该研究直接涉及情感计算中的多模态感知问题，提出了对抗性音频-文本对的基准测试和评估指标，具有具体证据支持。
行动建议 建议阅读相关文献，了解当前语音情感识别和音频LLM领域的研究进展，特别是关于跨模态冲突和文本偏见问题的研究。
证据与限制 证据层级为摘要描述，缺少具体实验细节和代码数据。可能失效条件包括：模型在不同数据集上的表现差异、评估指标的局限性以及对抗性音频-文本对的适用范围。
Lluna: Collaborative Unimodal Models for Missing-Modality InferenceLluna: Collaborative Unimodal Models for Missing-Modality Inference
Pretrained unimodal models offer a flexible route to multimodal prediction through collaboration, but this collaboration can become less accurate than a surviving unimodal model when modalities are missing. We study this setting using fixed surviving-model anchors and find that collaborative gains can weaken or reverse as inputs disappear, even when the anchor's own input is unchanged. Our diagnostics further reveal reduced...Pretrained unimodal models offer a flexible route to multimodal prediction through collaboration, but this collaboration can become less accurate than a surviving unimodal model when modalities are missing. We study this setting using fixed surviving-model anchors and find that collaborative gains can weaken or reverse as inputs disappear, even when the anchor's own input is unchanged. Our diagnostics further reveal reduced...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
How Language-Independent Are Emotional Attributes? A Study on Training Data Scaling and Cross-Lingual GeneralizationHow Language-Independent Are Emotional Attributes? A Study on Training Data Scaling and Cross-Lingual Generalization
Current state-of-the-art Speech Emotion Recognition (SER) systems rely on lots of training data, which is available only for a few languages such as English. For low-resource languages, using a cross-lingual model or adapting it to the target language might be an alternative to training a mono-lingual model from scratch. However, it is not clear what constitutes a "low-resource", i.e. where model adaptation loses its edge...Current state-of-the-art Speech Emotion Recognition (SER) systems rely on lots of training data, which is available only for a few languages such as English. For low-resource languages, using a cross-lingual model or adapting it to the target language might be an alternative to training a mono-lingual model from scratch. However, it is not clear what constitutes a "low-resource", i.e. where model adaptation loses its edge...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、具身与端侧产品、科研与开发提效
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Neurodiversity-Aware Multimodal Affective Computing for Neurodevelopmental Assessment: From Norm-Referenced Classification to Context-Sensitive Decision SupportNeurodiversity-Aware Multimodal Affective Computing for Neurodevelopmental Assessment: From Norm-Referenced Classification to Context-Sensitive Decision Support
Automated neurodevelopmental assessment increasingly combines computer vision, speech, eye tracking, physiology, and machine learning, yet multimodality and discrimination do not establish construct validity, clinical usefulness, or appropriate interpretation of behavioral variation. We propose a testable architecture for neurodiversity-aware multimodal affective computing in which population-relative deviation is not treated...Automated neurodevelopmental assessment increasingly combines computer vision, speech, eye tracking, physiology, and machine learning, yet multimodality and discrimination do not establish construct validity, clinical usefulness, or appropriate interpretation of behavioral variation. We propose a testable architecture for neurodiversity-aware multimodal affective computing in which population-relative deviation is not treated...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Automatic Evaluation of Mental Health Stigma in Online CommunicationAutomatic Evaluation of Mental Health Stigma in Online Communication
Mental health stigma has profoundly harmful impacts but its complexity makes it difficult to evaluate. Stigma may involve explicit derogation, but also subtler forms of blame, fear, paternalistic pity, social distancing, structural exclusion, and discrimination. We introduce a theory-grounded benchmark for automatic evaluation of mental health stigma in online communication, consisting of naturally occurring online news and...Mental health stigma has profoundly harmful impacts but its complexity makes it difficult to evaluate. Stigma may involve explicit derogation, but also subtler forms of blame, fear, paternalistic pity, social distancing, structural exclusion, and discrimination. We introduce a theory-grounded benchmark for automatic evaluation of mental health stigma in online communication, consisting of naturally occurring online news and...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、科研与开发提效、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Empath: Tracing Multi-Level Emotion Dynamics in Crisis Counseling DialoguesEmpath: Tracing Multi-Level Emotion Dynamics in Crisis Counseling Dialogues
Emotion dynamics are critical for understanding crisis-support conversations, yet most computational work treats emotion as static utterance-level labels. We introduce EMPATH, a framework for understanding affective dynamics in mental health dialogues across three granularities: turn-level labels, transition probabilities, and global conversation archetypes. Applying EMPATH to text-based crisis conversations with...Emotion dynamics are critical for understanding crisis-support conversations, yet most computational work treats emotion as static utterance-level labels. We introduce EMPATH, a framework for understanding affective dynamics in mental health dialogues across three granularities: turn-level labels, transition probabilities, and global conversation archetypes. Applying EMPATH to text-based crisis conversations with...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Saurabhtbj1201/MindSpace-Digital-Mental-Health-Support-PlatformSaurabhtbj1201/MindSpace-Digital-Mental-Health-Support-Platform
The platform combines cutting-edge technology including AI, IoT, and data analytics to provide personalized mental health support, resources, and monitoring tools to help students manage their mental wellbeing effectively. Recent GitHub repository activity related to AI mental health digital wellbeing, updated within the latest 30-day window. Primary language: JavaScript.The platform combines cutting-edge technology including AI, IoT, and data analytics to provide personalized mental health support, resources, and monitoring tools to help students manage their mental wellbeing effectively. Recent GitHub repository activity related to AI mental health digital wellbeing, updated within the latest 30-day window. Primary language: JavaScript.
仓库公开说明 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、具身与端侧产品、科研与开发提效
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental HealthFrom Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Health
The rising global prevalence of mental health conditions, together with longstanding barriers in traditional healthcare, such as limited resources, high cost, stigma, and privacy concerns, has created an urgent need for accessible and scalable support. Large Language Models (LLMs) have emerged as a transformative technology with strong potential to democratize mental health support through advanced natural language...The rising global prevalence of mental health conditions, together with longstanding barriers in traditional healthcare, such as limited resources, high cost, stigma, and privacy concerns, has created an urgent need for accessible and scalable support. Large Language Models (LLMs) have emerged as a transformative technology with strong potential to democratize mental health support through advanced natural language...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、具身与端侧产品、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
MIRA: Real-Time Full-Duplex Human-Robot Interaction for Embodied CompanionsMIRA: Real-Time Full-Duplex Human-Robot Interaction for Embodied Companions
% !TEX root = ../main.tex Real-time embodied companion interaction requires a robot to infer user intent from streaming speech, generate timely responses, and execute expressive, interruptible motions. Existing systems typically decouple dialogue orchestration from gesture synthesis, relying on offline motion generation from complete audio. This separation leaves open how a deployed robot can dynamically synchronize response...% !TEX root = ../main.tex Real-time embodied companion interaction requires a robot to infer user intent from streaming speech, generate timely responses, and execute expressive, interruptible motions. Existing systems typically decouple dialogue orchestration from gesture synthesis, relying on offline motion generation from complete audio. This separation leaves open how a deployed robot can dynamically synchronize response...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、具身与端侧产品
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Toward Human-in-the-Loop Robot Failure Recovery: Bridging Communication Gaps in Human-Robot CollaborationToward Human-in-the-Loop Robot Failure Recovery: Bridging Communication Gaps in Human-Robot Collaboration
Robots can recover from failures by asking bystanders for help, but effective human-in-the-loop recovery requires communication that accounts for differences in people's knowledge. Prior inverse-semantics work generates requests using a single listener model, leaving differences in listener knowledge untested. We introduce Listener Differences in Human-Robot Interaction (LD-HRI), a game, dataset, and benchmark that evaluates...Robots can recover from failures by asking bystanders for help, but effective human-in-the-loop recovery requires communication that accounts for differences in people's knowledge. Prior inverse-semantics work generates requests using a single listener model, leaving differences in listener knowledge untested. We introduce Listener Differences in Human-Robot Interaction (LD-HRI), a game, dataset, and benchmark that evaluates...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、具身与端侧产品、科研与开发提效
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Building Trustworthy Mental Health Benchmarks on Bluesky: A Validation-Aware Weak-Supervision FrameworkBuilding Trustworthy Mental Health Benchmarks on Bluesky: A Validation-Aware Weak-Supervision Framework
Decentralized social media platforms create new opportunities and challenges for computational mental health research because data access, moderation, labeling, and deployment responsibilities are distributed across multiple technical and governance layers. This paper presents a validation-aware weak-supervision system for constructing and evaluating suicidal ideation (SI) and broader mental health (MH) disclosure benchmarks...Decentralized social media platforms create new opportunities and challenges for computational mental health research because data access, moderation, labeling, and deployment responsibilities are distributed across multiple technical and governance layers. This paper presents a validation-aware weak-supervision system for constructing and evaluating suicidal ideation (SI) and broader mental health (MH) disclosure benchmarks...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、科研与开发提效、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Beyond Baseline Severity: Temporal and Disease-Specific Predictors of Depression Outcomes Following Mindfulness InterventionsBeyond Baseline Severity: Temporal and Disease-Specific Predictors of Depression Outcomes Following Mindfulness Interventions
Depression severity among patients with chronic or acute medical conditions is influenced by a complex interaction of baseline psychological state, demographic characteristics, clinical context, and engagement with behavioral interventions. This paper presents an interpretable machine-learning analysis of a multi-center longitudinal clinical cohort to predict Beck Depression Inventory-II (BDI-II) scores at 12 and 24 weeks...Depression severity among patients with chronic or acute medical conditions is influenced by a complex interaction of baseline psychological state, demographic characteristics, clinical context, and engagement with behavioral interventions. This paper presents an interpretable machine-learning analysis of a multi-center longitudinal clinical cohort to predict Beck Depression Inventory-II (BDI-II) scores at 12 and 24 weeks...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、科研与开发提效、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Depressive symptoms are reflected differently across digital contextsDepressive symptoms are reflected differently across digital contexts
As more of everyday life takes place online, digital behavior may provide a potential window into how depressive symptoms are reflected in daily life. Yet digital mental health studies have produced mixed findings. These inconsistencies may partly reflect how digital behavior is measured: self reported use, single device studies, and aggregate screen time can obscure differences across devices, activities, and patterns of...As more of everyday life takes place online, digital behavior may provide a potential window into how depressive symptoms are reflected in daily life. Yet digital mental health studies have produced mixed findings. These inconsistencies may partly reflect how digital behavior is measured: self reported use, single device studies, and aggregate screen time can obscure differences across devices, activities, and patterns of...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、科研与开发提效、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
与中国科学技术大学联合研究成果被 TAC 录用CausalSymptom Accepted by IEEE Transactions on Affective Computing
CausalSymptom 面向临床访谈文本中的抑郁严重程度估计，研究因果解耦表示学习，连接临床对话、可解释建模与心理计算。CausalSymptom studies causal disentangled representation learning for depression severity estimation from transcribed clinical interviews, connecting clinical dialogue, interpretability, and psychological computing.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
ERMoV 情绪调节驱动对话情绪识别研究发表于 IEEE Transactions on Affective ComputingERMoV: Modeling Affective Mental States via Emotion Regulation for Dialogue Emotion Recognition Published in IEEE Transactions on Affective Computing
孙晓、刘旭雄、姜月琪合作论文 ERMoV 发表在 IEEE Transactions on Affective Computing，通过情绪调节机制建模情感心理状态，使对话情绪识别从浅层标签识别走向具有心理机制支撑的状态建模。Xiao Sun, Xuxiong Liu, and Yueqi Jiang published ERMoV in IEEE Transactions on Affective Computing, modeling affective mental states through emotion-regulation mechanisms for dialogue emotion recognition.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
解码情感，智惠身心Decoding Emotion, Empowering Mind-Body Health
外部报道以“具身情感交互大模型突破之路”为主线，梳理团队从情感机器人、中文情感资源，到普适心理计算、EmoAda、PsyCoLLM 与具身情感智能的长期建设。External coverage frames Professor Xiao Sun's team as a long-term builder of embodied emotional interaction models, linking affective robots, Chinese emotional resources, Ubiquitous Psychological Computing, EmoAda, PsyCoLLM, and embodied emotional intelligence.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、具身与端侧产品
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
共情水平对齐强化学习研究发表于 IEEE Transactions on Affective ComputingEmpathy Level Alignment via Reinforcement Learning Published in IEEE Transactions on Affective Computing
该 IEEE Transactions on Affective Computing 论文研究面向共情回复生成的共情水平强化学习对齐，支撑团队在情感支持智能体方向的长期积累。This IEEE Transactions on Affective Computing paper studies empathy-level alignment through reinforcement learning for empathetic response generation, supporting the lab's long-term work on emotional support agents.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、智能体与团队能力、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
PsycoLLM 心理理解与评估研究发表于 IEEE TCSSPsycoLLM Published in IEEE Transactions on Computational Social Systems
PsycoLLM 面向大语言模型的心理理解与评估能力增强，连接情感 NLP、心理评估和实验室普适心理计算平台方向。PsycoLLM enhances large language models for psychological understanding and evaluation, linking affective NLP, psychological assessment, and the lab's broader psychological computing platform direction.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互、科研与开发提效
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Leading AI Researcher Outlines Challenges of Digital Mental Health - Bowdoin CollegeLeading AI Researcher Outlines Challenges of Digital Mental Health - Bowdoin College
Leading AI Researcher Outlines Challenges of Digital Mental Health Bowdoin CollegeLeading AI Researcher Outlines Challenges of Digital Mental Health Bowdoin College
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、科研与开发提效、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
GeoMER: A Joint Euclidean-Hyperbolic Geometry Framework for Multimodal Emotion RecognitionGeoMER: A Joint Euclidean-Hyperbolic Geometry Framework for Multimodal Emotion Recognition
Multimodal Emotion Recognition (MER) aims to understand human emotions by integrating information from multiple modalities such as speech and text. Psychological studies suggest that emotions exhibit latent hierarchical structured relationships in their semantic representations. However, most MER approaches rely on Euclidean representations, which capture fine-grained cross-modal interactions but do not explicitly provide a...Multimodal Emotion Recognition (MER) aims to understand human emotions by integrating information from multiple modalities such as speech and text. Psychological studies suggest that emotions exhibit latent hierarchical structured relationships in their semantic representations. However, most MER approaches rely on Euclidean representations, which capture fine-grained cross-modal interactions but do not explicitly provide a...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
DualAffect: Dual-Path Paralinguistic Integration for Generative Audiovisual Emotion UnderstandingDualAffect: Dual-Path Paralinguistic Integration for Generative Audiovisual Emotion Understanding
Understanding human emotion is essential for multimodal systems that interpret both the content of an interaction and the speaker's expressive state. However, connecting paralinguistic cues to generated answers remains challenging, particularly when vocal expression diverges from visual appearance. We propose DualAffect, a dual-path architecture that integrates visually conditioned acoustic features and temporally organized...Understanding human emotion is essential for multimodal systems that interpret both the content of an interaction and the speaker's expressive state. However, connecting paralinguistic cues to generated answers remains challenging, particularly when vocal expression diverges from visual appearance. We propose DualAffect, a dual-path architecture that integrates visually conditioned acoustic features and temporally organized...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Predicting Mental Health Help-Seeking Behaviour on Reddit: A Survival Analysis of Linguistic and Behavioural SignalsPredicting Mental Health Help-Seeking Behaviour on Reddit: A Survival Analysis of Linguistic and Behavioural Signals
Most prior work on predicting mental health help-seeking treats it as post-hoc classification of users already active in clinical communities, which cannot tell whether someone approaching a transition can be identified in advance. We instead frame help-seeking as a time-to-event problem and ask which Reddit users will eventually seek mental health support, and how imminent that transition is. We build a two-arm cohort: a...Most prior work on predicting mental health help-seeking treats it as post-hoc classification of users already active in clinical communities, which cannot tell whether someone approaching a transition can be identified in advance. We instead frame help-seeking as a time-to-event problem and ask which Reddit users will eventually seek mental health support, and how imminent that transition is. We build a two-arm cohort: a...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
AI Representations of Mental Health Stigma: Quantifying the Gap Between AI Estimations and Human Perceptions Across Gender Groups Using GPT-Based LLMsAI Representations of Mental Health Stigma: Quantifying the Gap Between AI Estimations and Human Perceptions Across Gender Groups Using GPT-Based LLMs
The increasing use of artificial intelligence (AI) in mental health applications raises concerns about its potential to internalize and perpetuate societal biases. This research evaluates both disparities and misalignment in how large language models (LLMs), GPT-4 and GPT-5, represent perceptions of mental health across gender groups. The research comprises two studies. Study 1 applied widely adopted measures of Social...The increasing use of artificial intelligence (AI) in mental health applications raises concerns about its potential to internalize and perpetuate societal biases. This research evaluates both disparities and misalignment in how large language models (LLMs), GPT-4 and GPT-5, represent perceptions of mental health across gender groups. The research comprises two studies. Study 1 applied widely adopted measures of Social...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Brain2Face: A Study on the Relation of EEG Signals and Spatio-temporal Head AvatarsBrain2Face: A Study on the Relation of EEG Signals and Spatio-temporal Head Avatars
Driving digital head avatars is classically done by hand-crafted artist design or by image-based facial performance capture. In this work, we ask whether spatio-temporal tracking of the humans's head geometry and appearance can be performed solely from brain signals, i.e., Electroencephalography (EEG). Since prior work mostly focused on activity and emotion recognition, this task is relatively unexplored without even having...Driving digital head avatars is classically done by hand-crafted artist design or by image-based facial performance capture. In this work, we ask whether spatio-temporal tracking of the humans's head geometry and appearance can be performed solely from brain signals, i.e., Electroencephalography (EEG). Since prior work mostly focused on activity and emotion recognition, this task is relatively unexplored without even having...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
China's Nine Government Departments Back Embodied AI; Unitree Robotics Surges Over 11% Intraday as Market Cap Tops 190 Billion Yuan - BigGo FinanceChina's Nine Government Departments Back Embodied AI; Unitree Robotics Surges Over 11% Intraday as Market Cap Tops 190 Billion Yuan - BigGo Finance
China's Nine Government Departments Back Embodied AI; Unitree Robotics Surges Over 11% Intraday as Market Cap Tops 190 Billion Yuan BigGo FinanceChina's Nine Government Departments Back Embodied AI; Unitree Robotics Surges Over 11% Intraday as Market Cap Tops 190 Billion Yuan BigGo Finance
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品
阅读建议 核对延迟、硬件条件、功耗和交互任务，再评估能否迁移到现有设备。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Advancing coding in low‑resource programming languagesAdvancing coding in low‑resource programming languages
Learn how OpenAI is improving ChatGPT across low-resource programming languages, with new evaluations for software engineering, SQLite, and COBOL migration.Learn how OpenAI is improving ChatGPT across low-resource programming languages, with new evaluations for software engineering, SQLite, and COBOL migration.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 科研复现、开发工具与资源管理。匹配：科研与开发提效
阅读建议 先核对许可、依赖与复现条件；若适用，用隔离的小任务验证时间和资源收益。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Making the internet better for AI agents might make it worse for everyone elseMaking the internet better for AI agents might make it worse for everyone else
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Until recently, you could divide internet users into just two categories: bots and people. Websites have long allowed bots to perform automated tasks, like capturing the content of web pages, but rules…This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Until recently, you could divide internet users into just two categories: bots and people. Websites have long allowed bots to perform automated tasks, like capturing the content of web pages, but rules…
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
AI researchers stranded Claude on a virtual desert island. It started to “play.”AI researchers stranded Claude on a virtual desert island. It started to “play.”
What do AI agents do if you don’t tell them to do anything? The answer looks a lot like play. Researchers repeatedly stranded them alone on a virtual desert island for 30 hours in an experiment reminiscent of the movies Cast Away or Home Alone. The agents—copies of Claude Opus 4.7 nicknamed Eko—were able to…What do AI agents do if you don’t tell them to do anything? The answer looks a lot like play. Researchers repeatedly stranded them alone on a virtual desert island for 30 hours in an experiment reminiscent of the movies Cast Away or Home Alone. The agents—copies of Claude Opus 4.7 nicknamed Eko—were able to…
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
MiniMax M3.1 FlashMiniMax M3.1 Flash
--- Top Comments --- [DCKing]: This model seems to be pretty benchmaxed. In actual use, it doesn't survive the comparison to models in the benchmark. This model was released as a "stealth model" in OpenCode Go for a while as "Space Bunny" (they mention this in the blog). So people have been using without knowing what the model was exactly, but it failed to impress anyone as far as I can tell. This is despite the model being served for free (with some asterisks). GLM 5.3 Flash and DeepSeek V4.1 Flas... [Perenti]: I'm finding these LLM announcements to be pretty meaningless. They all look the same, with different numbers and graphs, even though the graphs are almost all identical. The offered model is compared with models that it can beat, wi--- Top Comments --- [DCKing]: This model seems to be pretty benchmaxed. In actual use, it doesn't survive the comparison to models in the benchmark. This model was released as a "stealth model" in OpenCode Go for a while as "Space Bunny" (they mention this in the blog). So people have been using without knowing what the model was exactly, but it failed to impress anyone as far as I can tell. This is despite the model being served for free (with some asterisks). GLM 5.3 Flash and DeepSeek V4.1 Flas... [Perenti]: I'm finding these LLM announcements to be pretty meaningless. They all look the same, with different numbers and graphs, even though the graphs are almost all identical. The offered model is compared with models that it can beat, wi
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 科研复现、开发工具与资源管理。匹配：科研与开发提效
阅读建议 先核对许可、依赖与复现条件；若适用，用隔离的小任务验证时间和资源收益。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
I built a drone with only one motor [video]I built a drone with only one motor [video]
--- Top Comments --- [mrandish]: Just want to mention that hobbyists into fixed wing RC aerobatics have been doing crazy stuff with variable pitch propellers (VPP) for several years. RC motors with integrated variable pitch propellers exist in small sizes, so no need to DIY the propeller for that application. Here's an example of the 4D aerobatics they enable: https://www.youtube.com/watch?v=j5EsvZNvVRs . This is similar to but different than what the creator of the one motor drone is doing since he'... [TGower]: Underactuated robotics are so cool. In the hobby BattleBots community, there is a design where the whole robot only has a single motor, but it's able to move in any direction and damage the opponent, all just by controlling the sin--- Top Comments --- [mrandish]: Just want to mention that hobbyists into fixed wing RC aerobatics have been doing crazy stuff with variable pitch propellers (VPP) for several years. RC motors with integrated variable pitch propellers exist in small sizes, so no need to DIY the propeller for that application. Here's an example of the 4D aerobatics they enable: https://www.youtube.com/watch?v=j5EsvZNvVRs . This is similar to but different than what the creator of the one motor drone is doing since he'... [TGower]: Underactuated robotics are so cool. In the hobby BattleBots community, there is a design where the whole robot only has a single motor, but it's able to move in any direction and damage the opponent, all just by controlling the sin
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品
阅读建议 核对延迟、硬件条件、功耗和交互任务，再评估能否迁移到现有设备。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Welcome Muse Spark Open: open-weight frontier multimodal mixture-of-experts model from MetaWelcome Muse Spark Open: open-weight frontier multimodal mixture-of-experts model from Meta
来自 Hugging Face Blog 公开订阅源，内容与 Open-Source AI 及应用型 AI 系统建设相关。Selected from Hugging Face Blog's public feed for its relevance to Open-Source AI and applied AI systems.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Granite Switch 4.1: Chat, Decisions, and Speech from One EndpointGranite Switch 4.1: Chat, Decisions, and Speech from One Endpoint
来自 Hugging Face Blog 公开订阅源，内容与 Open-Source AI 及应用型 AI 系统建设相关。Selected from Hugging Face Blog's public feed for its relevance to Open-Source AI and applied AI systems.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
The Mood Matrix: Emotion AI for Next-Gen Retail Omnichannel - NasscomThe Mood Matrix: Emotion AI for Next-Gen Retail Omnichannel - Nasscom
The Mood Matrix: Emotion AI for Next-Gen Retail Omnichannel NasscomThe Mood Matrix: Emotion AI for Next-Gen Retail Omnichannel Nasscom
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
FACES: Fine-grained Gated Semantic Alignment for Multimodal Emotional Support ConversationFACES: Fine-grained Gated Semantic Alignment for Multimodal Emotional Support Conversation
In recent years, with advances in multimodal interaction technologies and the growing demand for intelligent emotional support, Multimodal Emotional Support Conversation (MESC) has emerged as an important task. However, existing systems still suffer from shallow responses and inappropriate support strategies due to weak semantic feedback, cross-dimension reward compensation, and coarse reasoning supervision. To address these...In recent years, with advances in multimodal interaction technologies and the growing demand for intelligent emotional support, Multimodal Emotional Support Conversation (MESC) has emerged as an important task. However, existing systems still suffer from shallow responses and inappropriate support strategies due to weak semantic feedback, cross-dimension reward compensation, and coarse reasoning supervision. To address these...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
PAT: A Personality-Driven Augmentation and Transfer Learning Framework for Depression Detection on Social MediaPAT: A Personality-Driven Augmentation and Transfer Learning Framework for Depression Detection on Social Media
Depression is a prevalent mental disorder that affects millions worldwide, with early detection crucial for effective intervention. While exist?ing methods have achieved promising results in automated depression detection, they face two key limitations: (1) noise in post screening: symptom-based semantic screening is easily misled by superficial lexical patterns, thereby introducing false-positive posts; (2) weak...Depression is a prevalent mental disorder that affects millions worldwide, with early detection crucial for effective intervention. While exist?ing methods have achieved promising results in automated depression detection, they face two key limitations: (1) noise in post screening: symptom-based semantic screening is easily misled by superficial lexical patterns, thereby introducing false-positive posts; (2) weak...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
From Surface to Depth: Towards Cognitive Appraisal Reasoning in Multimodal Emotion UnderstandingFrom Surface to Depth: Towards Cognitive Appraisal Reasoning in Multimodal Emotion Understanding
Recent multimodal large language models (MLLMs) increasingly incorporate explainable reasoning for emotion understanding. However, reasoning based mainly on observable affective cues can reduce emotion understanding to superficial cue-label associations, giving rise to the Clever Hans effect. Such shortcuts become unreliable when affective cues are implicit, conflicting across modalities, linguistically misleading, or...Recent multimodal large language models (MLLMs) increasingly incorporate explainable reasoning for emotion understanding. However, reasoning based mainly on observable affective cues can reduce emotion understanding to superficial cue-label associations, giving rise to the Clever Hans effect. Such shortcuts become unreliable when affective cues are implicit, conflicting across modalities, linguistically misleading, or...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Cognition-Oriented Emotion Tracing from Causes to Consequences in Real-World Social ScenesCognition-Oriented Emotion Tracing from Causes to Consequences in Real-World Social Scenes
Affective computing has progressed from categorical emotion recognition to open-ended affective analysis with large multimodal models. Yet affective science describes emotion as an unfolding process shaped by appraisal, regulation, and social interpretation, which remains underexplored computationally. We propose TRACE, a cognition-oriented framework that formalizes an affective episode through three interrelated stages:...Affective computing has progressed from categorical emotion recognition to open-ended affective analysis with large multimodal models. Yet affective science describes emotion as an unfolding process shaped by appraisal, regulation, and social interpretation, which remains underexplored computationally. We propose TRACE, a cognition-oriented framework that formalizes an affective episode through three interrelated stages:...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Bridging Human and Model Attention: Explainability Analysis of CNN, Mamba, and ViT Architectures with Gaze-Based ValidationBridging Human and Model Attention: Explainability Analysis of CNN, Mamba, and ViT Architectures with Gaze-Based Validation
High-risk applications of deep learning require precise characterization of model decision-making. We conduct a systematic explainability evaluation across Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), and Vision Mamba (ViM). Unlike predominantly qualitative studies, we quantify the alignment between model attention and human visual perception using eye-tracking ground truth. We formalize this comparison...High-risk applications of deep learning require precise characterization of model decision-making. We conduct a systematic explainability evaluation across Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), and Vision Mamba (ViM). Unlike predominantly qualitative studies, we quantify the alignment between model attention and human visual perception using eye-tracking ground truth. We formalize this comparison...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 科研复现、开发工具与资源管理。匹配：科研与开发提效、跨学科与产业转化
阅读建议 先核对许可、依赖与复现条件；若适用，用隔离的小任务验证时间和资源收益。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real HarnessesAgent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training...Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training...
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力、科研与开发提效、跨学科与产业转化
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
From Digital Human Interactions to Physics-Based Humanoid Skills: Physics-Grounded Post-Training of Interaction GeneratorsFrom Digital Human Interactions to Physics-Based Humanoid Skills: Physics-Grounded Post-Training of Interaction Generators
Recent methods have made promising progress in generating interactions between two humanoids, largely relying on physics-based tracking policies to convert digital reference motions into executable trajectories. However, limited tracking capabilities restrict the range of reference motions that can be successfully executed, reducing data utilization. Moreover, even successful tracking does not guarantee physically plausible...Recent methods have made promising progress in generating interactions between two humanoids, largely relying on physics-based tracking policies to convert digital reference motions into executable trajectories. However, limited tracking capabilities restrict the range of reference motions that can be successfully executed, reducing data utilization. Moreover, even successful tracking does not guarantee physically plausible...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力、科研与开发提效
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
When Layer Selection Misleads Speech Depression DetectionWhen Layer Selection Misleads Speech Depression Detection
Pretrained speech representations are increasingly used for depression detection, but selecting the best encoder layer on the same data used for evaluation biases reported performance. On DAIC-WOZ, with repeated nested cross-validation across five deep encoder families, naive best-of-25-layer probing inflates AUC by up to $0.09$. On shuffled labels over the \emph{real} latent representations, naive best-of-25 still reaches...Pretrained speech representations are increasingly used for depression detection, but selecting the best encoder layer on the same data used for evaluation biases reported performance. On DAIC-WOZ, with repeated nested cross-validation across five deep encoder families, naive best-of-25-layer probing inflates AUC by up to $0.09$. On shuffled labels over the \emph{real} latent representations, naive best-of-25 still reaches...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
kylelyhui-hub/Msc-CE901-Final-Projectkylelyhui-hub/Msc-CE901-Final-Project
This project proposes the development of a multimodal AI system for real‑time driver emotion regulation, integrating affective computing, behavior prediction, and adaptive intervention models into a unified framework. Recent GitHub repository activity related to affective computing emotion AI, updated within the latest 30-day window. Primary language: Python.This project proposes the development of a multimodal AI system for real‑time driver emotion regulation, integrating affective computing, behavior prediction, and adaptive intervention models into a unified framework. Recent GitHub repository activity related to affective computing emotion AI, updated within the latest 30-day window. Primary language: Python.
仓库公开说明 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
From Speech to Editable Concepts: Probing Emotion Recognition with Concept Bottleneck ModelsFrom Speech to Editable Concepts: Probing Emotion Recognition with Concept Bottleneck Models
Speech emotion recognition (SER) is the task of assigning emotion labels to utterances. Early systems relied on acoustic features, whereas recent approaches combine multiple modalities, most commonly speech and text. Still, performance remains poor on many datasets. Large language models (LLMs) have therefore attracted interest for SER, as they can process diverse inputs jointly with instructions. However, direct audio input...Speech emotion recognition (SER) is the task of assigning emotion labels to utterances. Early systems relied on acoustic features, whereas recent approaches combine multiple modalities, most commonly speech and text. Still, performance remains poor on many datasets. Large language models (LLMs) have therefore attracted interest for SER, as they can process diverse inputs jointly with instructions. However, direct audio input...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
DiFF: Doppler-informed Flow Matching for Human Motion FlowDiFF: Doppler-informed Flow Matching for Human Motion Flow
Perceiving human motion via privacy-preserving 4D millimeter-wave (mmWave) radar is critical for next-generation human-robot interaction (HRI), where point cloud scene flow serves as a foundational motion representation. Yet the extreme sparsity and noise of 4D radar point clouds make non-rigid motion flow estimation severely ill-posed--a challenge that existing rigid-centric methods and prior works fail to adequately...Perceiving human motion via privacy-preserving 4D millimeter-wave (mmWave) radar is critical for next-generation human-robot interaction (HRI), where point cloud scene flow serves as a foundational motion representation. Yet the extreme sparsity and noise of 4D radar point clouds make non-rigid motion flow estimation severely ill-posed--a challenge that existing rigid-centric methods and prior works fail to adequately...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、具身与端侧产品
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Rethinking Legibility in Social Robot Hallway Navigation: Impact of Intent Representation and Human DistractionRethinking Legibility in Social Robot Hallway Navigation: Impact of Intent Representation and Human Distraction
We focus on legible robot motion generation in social navigation settings. Legibility in human-robot interaction (HRI) is often described as the property of robot motion that enables an observer to confidently infer the robot's intent. While mature frameworks exist for generating legible motion in front of static observers, social robot navigation presents a new challenge: the robot must clearly convey its intent while...We focus on legible robot motion generation in social navigation settings. Legibility in human-robot interaction (HRI) is often described as the property of robot motion that enables an observer to confidently infer the robot's intent. While mature frameworks exist for generating legible motion in front of static observers, social robot navigation presents a new challenge: the robot must clearly convey its intent while...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、具身与端侧产品
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
MERID: Multimodal Exploration via Recursive Self-Improvement Agents for Major Depression AnalysisMERID: Multimodal Exploration via Recursive Self-Improvement Agents for Major Depression Analysis
Major depressive disorder (MDD) severely impacts daily activities and quality of life. Detecting MDD involves multimodal data, such as interview recordings and sensor measurements. This is particularly challenging, as these heterogeneous modalities often demand distinct, customized prediction pipelines. Existing efforts to address this challenge have explored both manually engineered multimodal architectures and...Major depressive disorder (MDD) severely impacts daily activities and quality of life. Detecting MDD involves multimodal data, such as interview recordings and sensor measurements. This is particularly challenging, as these heterogeneous modalities often demand distinct, customized prediction pipelines. Existing efforts to address this challenge have explored both manually engineered multimodal architectures and...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、智能体与团队能力
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
AquaWAM: A Dynamics-aware World Action Model for Underwater Embodied AgentsAquaWAM: A Dynamics-aware World Action Model for Underwater Embodied Agents
World Action Models (WAMs) are becoming increasingly important and useful for embodied intelligence, as they enable robots to anticipate the consequences of candidate actions before interacting with the physical environment. However, underwater robots are usually subject to passive dynamics, such as inertia, buoyancy, hydrodynamic drag, and persistent drift, which can continue to affect the vehicle even after an action is...World Action Models (WAMs) are becoming increasingly important and useful for embodied intelligence, as they enable robots to anticipate the consequences of candidate actions before interacting with the physical environment. However, underwater robots are usually subject to passive dynamics, such as inertia, buoyancy, hydrodynamic drag, and persistent drift, which can continue to affect the vehicle even after an action is...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力、具身与端侧产品
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
WSM-Aware HRI: An IoT-Enhanced Framework for Early Detection and Norm-Guided Repair of Failures with LLM GuidanceWSM-Aware HRI: An IoT-Enhanced Framework for Early Detection and Norm-Guided Repair of Failures with LLM Guidance
Human-robot interaction (HRI) failures remain a major barrier to deploying robots in real-world environments. Prior work often treats failures as isolated technical faults or focuses on post-hoc recovery behaviors. In practice, many breakdowns arise because humans and robots operate under inconsistent assumptions about the current world state. We propose WSM-Aware HRI, an IoT-enhanced modular framework that unifies diverse...Human-robot interaction (HRI) failures remain a major barrier to deploying robots in real-world environments. Prior work often treats failures as isolated technical faults or focuses on post-hoc recovery behaviors. In practice, many breakdowns arise because humans and robots operate under inconsistent assumptions about the current world state. We propose WSM-Aware HRI, an IoT-enhanced modular framework that unifies diverse...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、具身与端侧产品
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Evaluating the Impact of Adaptive Extended Reality on Human-Robot Interaction Across the Reality-Virtuality ContinuumEvaluating the Impact of Adaptive Extended Reality on Human-Robot Interaction Across the Reality-Virtuality Continuum
As populations in developed countries age and labor shortages intensify, Cybernetic Avatars (CAs) are proposed to extend human capabilities through robotic embodiments, requiring effective Human-Robot Interaction (HRI) frameworks. Extended Reality (XR), an umbrella term for Augmented Reality (AR), Augmented Virtuality (AV), and Virtual Reality (VR), offers such interfaces, but prior research typically fixes the XR modality...As populations in developed countries age and labor shortages intensify, Cybernetic Avatars (CAs) are proposed to extend human capabilities through robotic embodiments, requiring effective Human-Robot Interaction (HRI) frameworks. Extended Reality (XR), an umbrella term for Augmented Reality (AR), Augmented Virtuality (AV), and Virtual Reality (VR), offers such interfaces, but prior research typically fixes the XR modality...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、具身与端侧产品
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Benchmarking Robots for Everyday Environments: From Lab Experiments to Real-World OperationsBenchmarking Robots for Everyday Environments: From Lab Experiments to Real-World Operations
This study presents an interdisciplinary process for benchmarking service robots in public everyday environments, addressing the gap between laboratory metrics and real-world operation at technology readiness levels 6-7. Three robots were evaluated in three use cases: outdoor park cleaning, pedestrian underpass cleaning, and interactive assistance in a public library. Over three years (2023-2025), seven benchmarking events (a...This study presents an interdisciplinary process for benchmarking service robots in public everyday environments, addressing the gap between laboratory metrics and real-world operation at technology readiness levels 6-7. Three robots were evaluated in three use cases: outdoor park cleaning, pedestrian underpass cleaning, and interactive assistance in a public library. Over three years (2023-2025), seven benchmarking events (a...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品、科研与开发提效
阅读建议 核对延迟、硬件条件、功耗和交互任务，再评估能否迁移到现有设备。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Can I Trust My Body? A Three-Year Autoethnography of ChatGPT's Place in My Support System for Panic AttacksCan I Trust My Body? A Three-Year Autoethnography of ChatGPT's Place in My Support System for Panic Attacks
People increasingly seek mental health support from large language models, yet little is known about their use across years of recurrent panic. We present a three-year analytic autoethnography of the first author's ChatGPT use while living with panic disorder, drawing on conversations, personal records, and accounts from friends or family members and professionals. Narrative analysis traces how my questions shaped ChatGPT's...People increasingly seek mental health support from large language models, yet little is known about their use across years of recurrent panic. We present a three-year analytic autoethnography of the first author's ChatGPT use while living with panic disorder, drawing on conversations, personal records, and accounts from friends or family members and professionals. Narrative analysis traces how my questions shaped ChatGPT's...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Understanding Engagement and Intrusiveness in Assistive Human-Robot Interaction Using Individual TraitsUnderstanding Engagement and Intrusiveness in Assistive Human-Robot Interaction Using Individual Traits
Robot assistance is particularly crucial in unfamiliar tasks, where users must understand task requirements while coordinating with the robot. Previous research offers mixed evidence on the role of robot proxemics in user engagement: some studies suggest closer proximity enhances interaction, while others report it can feel intrusive. In this work, we argue that perceptions of intrusiveness depend not only on proxemics but...Robot assistance is particularly crucial in unfamiliar tasks, where users must understand task requirements while coordinating with the robot. Previous research offers mixed evidence on the role of robot proxemics in user engagement: some studies suggest closer proximity enhances interaction, while others report it can feel intrusive. In this work, we argue that perceptions of intrusiveness depend not only on proxemics but...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、具身与端侧产品
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Causal-ESC 情感支持对话因果检测研究发表于 IEEE/ACM TASLPCausal-ESC Accepted by IEEE/ACM Transactions on Audio, Speech, and Language Processing
Causal-ESC 面向情感支持对话中的因果动态检测，连接情感 NLP、共情对话与具有心理意义的交互建模。Causal-ESC captures cause-and-effect dynamics in emotional support conversation, connecting affective NLP, empathetic dialogue, and psychologically meaningful interaction modeling.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、心智与人机交互
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
MultiAgentESC 情感支持对话多智能体框架发表于 EMNLP 2025MultiAgentESC Accepted by EMNLP 2025
MultiAgentESC 提出面向情感支持对话的大语言模型多智能体协作框架，推动 MAC-Lab 情感 NLP 路线走向更结构化的情感支持智能体。MultiAgentESC proposes a large-language-model-based multi-agent collaboration framework for emotional support conversation, extending MAC-Lab's affective NLP route toward more structured emotional support agents.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、智能体与团队能力
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
UniEmoX 发表在 IEEE Transactions on Image ProcessingUniEmoX Published in IEEE Transactions on Image Processing
指导论文 UniEmoX 面向通用场景情绪感知与跨模态语义预训练，发表于 CCF A 类期刊 IEEE Transactions on Image Processing。The student-guided work UniEmoX studies cross-modal semantic-guided large-scale pretraining for universal scene emotion perception, strengthening the lab's publication portfolio in affective visual intelligence.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、科研与开发提效
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
社会-心理双维聚类建模研究发表于 IPMLP 2025Social-Psychological Dual-Dimensional Clustering Modeling Published at IPMLP 2025
该会议论文通过社会-心理双维聚类与机器学习分析戒烟成功异质性，把心理计算能力延伸到健康行为分析场景。The conference paper studies heterogeneity in smoking-cessation success through social-psychological dual-dimensional clustering and machine learning, extending psychological computing into health-behavior analysis.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Eye Tracking and Affective Computing Reveal Learner Attention States - Bioengineer.orgEye Tracking and Affective Computing Reveal Learner Attention States - Bioengineer.org
Eye Tracking and Affective Computing Reveal Learner Attention States Bioengineer.orgEye Tracking and Affective Computing Reveal Learner Attention States Bioengineer.org
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Press Release: Tom Kean Jr. Hosts Roundtable on Childhood Mental Health - Quiver QuantitativePress Release: Tom Kean Jr. Hosts Roundtable on Childhood Mental Health - Quiver Quantitative
Press Release: Tom Kean Jr. Hosts Roundtable on Childhood Mental Health Quiver QuantitativePress Release: Tom Kean Jr. Hosts Roundtable on Childhood Mental Health Quiver Quantitative
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Run fast, private agents on-device with LFM2.5-24B-A2BRun fast, private agents on-device with LFM2.5-24B-A2B
来自 Hugging Face Blog 公开订阅源，内容与 Open-Source AI 及应用型 AI 系统建设相关。Selected from Hugging Face Blog's public feed for its relevance to Open-Source AI and applied AI systems.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力、科研与开发提效
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Empathy Is Not the Scapegoat for Declines in Factuality and ReliabilityEmpathy Is Not the Scapegoat for Declines in Factuality and Reliability
Language models are increasingly expected to support users in stressful or uncertain situations, where warmth and empathy are desirable. While recent work associates warmer models with reduced reliability, we show that this conclusion is incomplete. Prior studies often train primarily on empathetic dialogue, making it difficult to separate tone effects from SFT-induced distribution shift. We revisit this issue at both the...Language models are increasingly expected to support users in stressful or uncertain situations, where warmth and empathy are desirable. While recent work associates warmer models with reduced reliability, we show that this conclusion is incomplete. Prior studies often train primarily on empathetic dialogue, making it difficult to separate tone effects from SFT-induced distribution shift. We revisit this issue at both the...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Hong Kong vies for role in robot boom with embodied AI hub launch - South China Morning PostHong Kong vies for role in robot boom with embodied AI hub launch - South China Morning Post
Hong Kong vies for role in robot boom with embodied AI hub launch South China Morning PostHong Kong vies for role in robot boom with embodied AI hub launch South China Morning Post
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品
阅读建议 核对延迟、硬件条件、功耗和交互任务，再评估能否迁移到现有设备。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Itaú 使用 AI 增强客户和员工互动How Itaú is building generative AI for its entire customer base
Itaú 正在使用 AI 通过对话界面和治理平台来增强客户和员工的互动，但文章没有提供具体的实施细节。With ia.i, a conversational interface, and the IARA governance platform, Itaú is applying its AI First strategy to customers and employees — in one of Brazil’s most regulated sectors.
公开来源摘录 · Horizon 模型解读 · 请核对原文
与我们有什么关系 · 怎样用Relevance & next step
关联方向 跨学科方法与产品落地。匹配：跨学科与产业转化
原文要点 Itaú 正在使用 AI 通过对话界面和治理平台来增强客户和员工的互动，但文章没有提供具体的实施细节。
研究关联 Itaú 的 AI 战略在巴西银行业这样一个高度监管的领域中应用，与 AI 治理和对话式 AI 的研究方向密切相关。
行动建议 建议阅读更多关于 Itaú 的 AI 治理平台 IARA 和对话界面 ia.i 的具体技术细节。
证据与限制 文章缺乏具体的实施细节和技术方法，证据层级较低，无法提供详细的验证依据。可能失效条件包括技术细节的缺失和监管环境的变化。
Stack Overflow for Agents triples signups with ChatGPT pluginStack Overflow for Agents triples signups with ChatGPT plugin
Two engineers shipped Stack Overflow for Agents in a few weeks with Codex, and its ChatGPT plugin helped drive up to 10× growth in agent creation.Two engineers shipped Stack Overflow for Agents in a few weeks with Codex, and its ChatGPT plugin helped drive up to 10× growth in agent creation.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Grounding AI agents in biological reality: Building blocks for autonomous wet labsGrounding AI agents in biological reality: Building blocks for autonomous wet labs
来自 Google Research 公开订阅源，内容与 AI Research 及应用型 AI 系统建设相关。Selected from Google Research's public feed for its relevance to AI Research and applied AI systems.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Video Friday: When Two Robots Become OneVideo Friday: When Two Robots Become One
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. CoRL 2026 : 9–12 November 2026, AUSTIN Humanoids 2026 : 6–9 December 2026, SANTA CLARA, CA Enjoy today’s videos!...Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. CoRL 2026 : 9–12 November 2026, AUSTIN Humanoids 2026 : 6–9 December 2026, SANTA CLARA, CA Enjoy today’s videos!...
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品
阅读建议 核对延迟、硬件条件、功耗和交互任务，再评估能否迁移到现有设备。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Wine ported to OpenBSDWine ported to OpenBSD
--- Top Comments --- [haunter]: Gameplay videos Disco Elysium https://video.gamerstavern.online/w/qYjXr8dBauynzvEquJ7cP4 Hollow Knight https://video.gamerstavern.online/w/8tjjFRDtGJQZwxfE4ojVoC Prey 2017 https://video.gamerstavern.online/w/vNxVThRcpijbT9FAQPcKdz Death Stranding https://video.gamerstavern.online/w/rzz2TLCxcmneHsydukAFLU Witcher 3 Remastered https://video.gamerstavern.online/w/oZcTRKL5JMiU4M4FqGKcNH A... [t-3]: https://marc.info/?l=openbsd-ports&m=179241414029592 > I doubt much will be merged upstream. Many updates we have can technically run on other OSes (%gs stubs won't be built on Linux because %gs is correctly set, SIGUSR1 will work but less optimally, etc). However I picked an approach where everything that is done for --- Top Comments --- [haunter]: Gameplay videos Disco Elysium https://video.gamerstavern.online/w/qYjXr8dBauynzvEquJ7cP4 Hollow Knight https://video.gamerstavern.online/w/8tjjFRDtGJQZwxfE4ojVoC Prey 2017 https://video.gamerstavern.online/w/vNxVThRcpijbT9FAQPcKdz Death Stranding https://video.gamerstavern.online/w/rzz2TLCxcmneHsydukAFLU Witcher 3 Remastered https://video.gamerstavern.online/w/oZcTRKL5JMiU4M4FqGKcNH A... [t-3]: https://marc.info/?l=openbsd-ports&m=179241414029592 > I doubt much will be merged upstream. Many updates we have can technically run on other OSes (%gs stubs won't be built on Linux because %gs is correctly set, SIGUSR1 will work but less optimally, etc). However I picked an approach where everything that is done for
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Android apps running native on macOSAndroid apps running native on macOS
--- Top Comments --- [qalmakka]: > Run Android apps natively on Apple Silicon Macs. No emulator, no virtual machine, no Linux underneath. God damnit Dario fix Claude already so that it stops using this sentence structure once and for all. Opus is so annoyingly recognisable that it has started to irk me badly lately [andsoitis]: > no virtual machine Android apps are usually written in Kotlin or Java, so this solution does not depend on the JVM? [bilalq]: In practice, the Google Play Services dependencies and other walled-garden initiatives from Google will make this less useful than it could otherwise be. But still, this is really cool. [publlus_enigma]: I can't take any more AI generated verbiage. My collection of pre-AI technical books and--- Top Comments --- [qalmakka]: > Run Android apps natively on Apple Silicon Macs. No emulator, no virtual machine, no Linux underneath. God damnit Dario fix Claude already so that it stops using this sentence structure once and for all. Opus is so annoyingly recognisable that it has started to irk me badly lately [andsoitis]: > no virtual machine Android apps are usually written in Kotlin or Java, so this solution does not depend on the JVM? [bilalq]: In practice, the Google Play Services dependencies and other walled-garden initiatives from Google will make this less useful than it could otherwise be. But still, this is really cool. [publlus_enigma]: I can't take any more AI generated verbiage. My collection of pre-AI technical books and
仓库公开说明 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Starcraft: AshfallStarcraft: Ashfall
--- Top Comments --- [ggnore7452]: Wow, thanks to whoever posted this! I made this game. Like many, I was frustrated there's no new StarCraft coming till 2030, so I half-jokingly made the mini-game those mobile ads always promise and never deliver. Something you can play with one hand, that your friends who've never played StarCraft can just pick up.(Turns out you can squeeze a lot of extra gameplay/design on top of it.) Also, if you're going to copy Blizzard you might as well copy the whole package right, ... [gbnwl]: Reddit thread from about a month ago where creator introduced this: https://www.reddit.com/r/starcraft/comments/1wqdabw/i_made_t... [neko_ranger]: Wow someone made the youtube ad game! [bulbar]: Cool visuals, but doesn't coun--- Top Comments --- [ggnore7452]: Wow, thanks to whoever posted this! I made this game. Like many, I was frustrated there's no new StarCraft coming till 2030, so I half-jokingly made the mini-game those mobile ads always promise and never deliver. Something you can play with one hand, that your friends who've never played StarCraft can just pick up.(Turns out you can squeeze a lot of extra gameplay/design on top of it.) Also, if you're going to copy Blizzard you might as well copy the whole package right, ... [gbnwl]: Reddit thread from about a month ago where creator introduced this: https://www.reddit.com/r/starcraft/comments/1wqdabw/i_made_t... [neko_ranger]: Wow someone made the youtube ad game! [bulbar]: Cool visuals, but doesn't coun
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Ukraine claims first drone evacuation of wounded soldierUkraine claims first drone evacuation of wounded soldier
--- Top Comments --- [1970-01-01]: If they can pull them out, they can also drop fresh ones down. Not sure if that is better than just using a helicopter however. [vzaliva]: It reaffirms that Ukrainians are: 1. very advanced with drones 2. caring about their soldiers Disclaimer: I am a proud Ukrainian. [expedition32]: I hope in the future all wars are fought by drones. Just don't make them unstoppable like in that Horizon videogame. [dgudkov]: Another Ukrainian innovation using drones: transporting transplant organs. https://ukrspecsystems.com/blog/pd-2-uav-tested-for-organ-de... [skeledrew]: NGL, reading this gave me the feels... Also, next wartime invention: air mines.--- Top Comments --- [1970-01-01]: If they can pull them out, they can also drop fresh ones down. Not sure if that is better than just using a helicopter however. [vzaliva]: It reaffirms that Ukrainians are: 1. very advanced with drones 2. caring about their soldiers Disclaimer: I am a proud Ukrainian. [expedition32]: I hope in the future all wars are fought by drones. Just don't make them unstoppable like in that Horizon videogame. [dgudkov]: Another Ukrainian innovation using drones: transporting transplant organs. https://ukrspecsystems.com/blog/pd-2-uav-tested-for-organ-de... [skeledrew]: NGL, reading this gave me the feels... Also, next wartime invention: air mines.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Wolf-Inspired AI Tuning Pushes Speech Emotion Recognition Across Languages and Labs - Bioengineer.orgWolf-Inspired AI Tuning Pushes Speech Emotion Recognition Across Languages and Labs - Bioengineer.org
Wolf-Inspired AI Tuning Pushes Speech Emotion Recognition Across Languages and Labs Bioengineer.orgWolf-Inspired AI Tuning Pushes Speech Emotion Recognition Across Languages and Labs Bioengineer.org
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Putting Earth AI to work: Geospatial agents for our planet's biggest challengesPutting Earth AI to work: Geospatial agents for our planet's biggest challenges
来自 Google Research 公开订阅源，内容与 AI Research 及应用型 AI 系统建设相关。Selected from Google Research's public feed for its relevance to AI Research and applied AI systems.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
HiPAD: A Unified Gait, Audio-Visual, and Personality Fusion Network for Depression Detection, with a Hierarchical Personality Ablation and the Calibration Limits of Domain-Adapted LLMsHiPAD: A Unified Gait, Audio-Visual, and Personality Fusion Network for Depression Detection, with a Hierarchical Personality Ablation and the Calibration Limits of Domain-Adapted LLMs
We present HiPAD, a single fusion network submitted to all six sub-tracks of the MPDD-AVG 2026 depression-detection challenge, covering the Elder and Young cohorts and three modality sets (gait, audio-visual, and both), each combined with personality descriptions. The network encodes each available modality with a shared BiLSTM, zero-pads absent modalities, and applies cross-modal attention only when at least two of gait,...We present HiPAD, a single fusion network submitted to all six sub-tracks of the MPDD-AVG 2026 depression-detection challenge, covering the Elder and Young cohorts and three modality sets (gait, audio-visual, and both), each combined with personality descriptions. The network encodes each available modality with a shared BiLSTM, zero-pads absent modalities, and applies cross-modal attention only when at least two of gait,...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Specification-Based Testing of Large Language ModelsSpecification-Based Testing of Large Language Models
Model cards, system cards, and safety reports increasingly document LLM safety behaviors, yet safety evaluations typically start from predefined benchmarks rather than asking which documented claims those benchmarks actually test. We introduce LEST (LLM Evaluation through Specification-driven Testing), a framework that treats documented safety claims as specifications for black-box testing. In LEST, each claim determines...Model cards, system cards, and safety reports increasingly document LLM safety behaviors, yet safety evaluations typically start from predefined benchmarks rather than asking which documented claims those benchmarks actually test. We introduce LEST (LLM Evaluation through Specification-driven Testing), a framework that treats documented safety claims as specifications for black-box testing. In LEST, each claim determines...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 科研复现、开发工具与资源管理。匹配：科研与开发提效
阅读建议 先核对许可、依赖与复现条件；若适用，用隔离的小任务验证时间和资源收益。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Evidential Multimodal Transformers with Dempster-Shafer Fusion for Emotion RecognitionEvidential Multimodal Transformers with Dempster-Shafer Fusion for Emotion Recognition
Softmax-based multimodal emotion recognition methods often assign high confidence even when sensor data are corrupted or contradictory, for example when facial expressions suggest positive valence while vocal prosody indicates negative arousal. We present an Evidential Multimodal Transformer with Dempster-Shafer Fusion (EMT-DS) that addresses this problem through formal uncertainty quantification. EMT-DS models predictions as...Softmax-based multimodal emotion recognition methods often assign high confidence even when sensor data are corrupted or contradictory, for example when facial expressions suggest positive valence while vocal prosody indicates negative arousal. We present an Evidential Multimodal Transformer with Dempster-Shafer Fusion (EMT-DS) that addresses this problem through formal uncertainty quantification. EMT-DS models predictions as...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Inside Track - Building trust in AI-powered support at Microsoft: Our Employee Self-Service agent story - MicrosoftInside Track - Building trust in AI-powered support at Microsoft: Our Employee Self-Service agent story - Microsoft
Inside Track - Building trust in AI-powered support at Microsoft: Our Employee Self-Service agent story MicrosoftInside Track - Building trust in AI-powered support at Microsoft: Our Employee Self-Service agent story Microsoft
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、智能体与团队能力
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
SEER: Source-Conditioned Emotion Enhancement via Retrieval for Cochlear-Implant SpeechSEER: Source-Conditioned Emotion Enhancement via Retrieval for Cochlear-Implant Speech
Cochlear implants (CIs) restore speech access but weaken cues needed for vocal emotion recognition. Prior CI-oriented enhancement requires parallel normal/strong recordings and intensity labels. We propose SEER, a retrieval-based framework that learns which same-emotion reference helps each source remain recognizable after CI processing. A source-conditioned retriever learns CI-aware utility from sampled emotional voice...Cochlear implants (CIs) restore speech access but weaken cues needed for vocal emotion recognition. Prior CI-oriented enhancement requires parallel normal/strong recordings and intensity labels. We propose SEER, a retrieval-based framework that learns which same-emotion reference helps each source remain recognizable after CI processing. A source-conditioned retriever learns CI-aware utility from sampled emotional voice...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Multi-Objective Aligned Small Language Model Framework for SUD Patient Dialogue GenerationMulti-Objective Aligned Small Language Model Framework for SUD Patient Dialogue Generation
Substance Use Disorder (SUD) counseling requires patient responses that reflect underlying cognitive states such as beliefs, coping strategies, and readiness for change. Although large language models (LLMs) can generate fluent text, they often fail to produce cognitively coherent and clinically realistic patient behavior, especially under ethical and data-scarce clinical settings. Moreover, deploying frontier-scale LLMs in...Substance Use Disorder (SUD) counseling requires patient responses that reflect underlying cognitive states such as beliefs, coping strategies, and readiness for change. Although large language models (LLMs) can generate fluent text, they often fail to produce cognitively coherent and clinically realistic patient behavior, especially under ethical and data-scarce clinical settings. Moreover, deploying frontier-scale LLMs in...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Planetary Geospatial Foundation Models: A New Paradigm for Global Public HealthPlanetary Geospatial Foundation Models: A New Paradigm for Global Public Health
The efficacy of traditional disease prediction is limited by spatial gaps and temporal lags, which impact the timing and targets of resource deployments. Outbreaks escalate undetected, chronic disease burdens are quantified years later, and at-risk populations in data-sparse regions remain unaddressed. Planetary geospatial foundation models complement existing epidemiological workflows to provide operational improvements,...The efficacy of traditional disease prediction is limited by spatial gaps and temporal lags, which impact the timing and targets of resource deployments. Outbreaks escalate undetected, chronic disease burdens are quantified years later, and at-risk populations in data-sparse regions remain unaddressed. Planetary geospatial foundation models complement existing epidemiological workflows to provide operational improvements,...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 跨学科方法与产品落地。匹配：跨学科与产业转化
阅读建议 找到可迁移的方法或真实需求，并记录与当前技术路线的差异。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
ParaCalib: Semantically Calibrated Paralinguistic Modeling for Depression DetectionParaCalib: Semantically Calibrated Paralinguistic Modeling for Depression Detection
Vocal behavior provides important signals for speech-based depression detection, but its interpretation often depends on what is being said and how it functions in context. However, existing methods typically treat acoustic cues as context-independent markers, making it difficult to distinguish vocal form from its context-dependent communicative function. We propose ParaCalib, a framework that semantically calibrates...Vocal behavior provides important signals for speech-based depression detection, but its interpretation often depends on what is being said and how it functions in context. However, existing methods typically treat acoustic cues as context-independent markers, making it difficult to distinguish vocal form from its context-dependent communicative function. We propose ParaCalib, a framework that semantically calibrates...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
AURAL: Adaptive Latent Reasoning with Joint Chunk for Speech Language ModelsAURAL: Adaptive Latent Reasoning with Joint Chunk for Speech Language Models
Model intelligence and fast response jointly shape the quality of interaction with speech language models, yet remain difficult to achieve together. Explicit chain-of-thought (CoT) improves reasoning and audio understanding, but generating intermediate reasoning tokens delays responses. Describing fine-grained acoustic cues further lengthens CoT and increases latency. Latent reasoning can reduce this overhead, yet existing...Model intelligence and fast response jointly shape the quality of interaction with speech language models, yet remain difficult to achieve together. Explicit chain-of-thought (CoT) improves reasoning and audio understanding, but generating intermediate reasoning tokens delays responses. Describing fine-grained acoustic cues further lengthens CoT and increases latency. Latent reasoning can reduce this overhead, yet existing...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Aligning the Incomplete: Joint Distribution Calibration for Multimodal EEG-Eye Emotion RecognitionAligning the Incomplete: Joint Distribution Calibration for Multimodal EEG-Eye Emotion Recognition
The success of cross-subject multimodal emotion recognition hinges on maintaining the consistency of the joint data distribution across individuals. However, real-world deployment frequently triggers the \emph{asymmetric joint distribution collapse}: EEG signals suffer from severe cross-subject distribution shifts, while eye movements sensors are susceptible to packet loss and tracking failures. Existing methods treat domain...The success of cross-subject multimodal emotion recognition hinges on maintaining the consistency of the joint data distribution across individuals. However, real-world deployment frequently triggers the \emph{asymmetric joint distribution collapse}: EEG signals suffer from severe cross-subject distribution shifts, while eye movements sensors are susceptible to packet loss and tracking failures. Existing methods treat domain...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
AI’s Mental Health Test— POLITICO - Dartmouth Geisel School of MedicineAI’s Mental Health Test— POLITICO - Dartmouth Geisel School of Medicine
AI’s Mental Health Test— POLITICO Dartmouth Geisel School of MedicineAI’s Mental Health Test— POLITICO Dartmouth Geisel School of Medicine
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
AI-Driven Collaborative Assembly Line Inspection: System Integration and Deployment ChallengesAI-Driven Collaborative Assembly Line Inspection: System Integration and Deployment Challenges
Manual visual inspection on assembly lines is a persistent manufacturing bottleneck: operator fatigue over extended shifts lowers defect-detection rates. This paper presents the design, integration, and field deployment of an AI-assisted collaborative inspection cell at the Silverline kitchen-appliance factory, developed within the AI-PRISM project. The cell couples a Universal Robots UR 10e cobot carrying a machine-vision...Manual visual inspection on assembly lines is a persistent manufacturing bottleneck: operator fatigue over extended shifts lowers defect-detection rates. This paper presents the design, integration, and field deployment of an AI-assisted collaborative inspection cell at the Silverline kitchen-appliance factory, developed within the AI-PRISM project. The cell couples a Universal Robots UR 10e cobot carrying a machine-vision...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品
阅读建议 核对延迟、硬件条件、功耗和交互任务，再评估能否迁移到现有设备。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Differential Attention Unlocks Complementary EEG and Speech Fusion for Emotion RecognitionDifferential Attention Unlocks Complementary EEG and Speech Fusion for Emotion Recognition
Multimodal emotion recognition (MER) increasingly pairs EEG with speech, treating internal neural signals and external vocal expression as informative views of affect. In practice, naive fusion underperforms the stronger single modality, because EEG artifacts inject noise that corrupts the shared representation. We introduce EmoSpeechBrain, a multimodal framework built on the insight that noise suppression is a precondition...Multimodal emotion recognition (MER) increasingly pairs EEG with speech, treating internal neural signals and external vocal expression as informative views of affect. In practice, naive fusion underperforms the stronger single modality, because EEG artifacts inject noise that corrupts the shared representation. We introduce EmoSpeechBrain, a multimodal framework built on the insight that noise suppression is a precondition...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Offloaded inference for real-world physical AI roboticsOffloaded inference for real-world physical AI robotics
Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads. The post Offloaded inference for real-world physical AI robotics appeared first on Microsoft Research .Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads. The post Offloaded inference for real-world physical AI robotics appeared first on Microsoft Research .
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品、科研与开发提效
阅读建议 核对延迟、硬件条件、功耗和交互任务，再评估能否迁移到现有设备。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
BiCFlow-MER: Orchestrating Discriminative and Generative Multimodal Emotion Recognition via Conditional TransportBiCFlow-MER: Orchestrating Discriminative and Generative Multimodal Emotion Recognition via Conditional Transport
In multimodal emotion recognition (MER), human affective states are inferred by integrating complementary cues from multiple modalities. In audio-text MER, affective cues are often entangled with speaker style and lexical content, while cross-modal disagreement further complicates how the evidence should be integrated. Under conventional discriminative fusion, multimodal evidence is compressed into a terminal prediction, with...In multimodal emotion recognition (MER), human affective states are inferred by integrating complementary cues from multiple modalities. In audio-text MER, affective cues are often entangled with speaker style and lexical content, while cross-modal disagreement further complicates how the evidence should be integrated. Under conventional discriminative fusion, multimodal evidence is compressed into a terminal prediction, with...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Poitras Center to fuel early careers of 50 young scientists dedicated to psychiatric disorders researchPoitras Center to fuel early careers of 50 young scientists dedicated to psychiatric disorders research
Patricia and James Poitras ’63 provide fellowships for graduate students and postdocs who will shape the future of mental health research.Patricia and James Poitras ’63 provide fellowships for graduate students and postdocs who will shape the future of mental health research.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互、跨学科与产业转化
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Enriching Speech Emotion Representations with Conversational ContextEnriching Speech Emotion Representations with Conversational Context
Detecting emotions is necessary for building systems that can accurately and adaptively interact with humans. Speech Emotion Recognition (SER) has become an important research focus to develop intelligent spoken interfaces. However, most studies predict emotions at the utterance level, ignoring the conversational context, along with the emotional flow and speaker interactions it carries. In this paper, we introduce ACERT...Detecting emotions is necessary for building systems that can accurately and adaptively interact with humans. Speech Emotion Recognition (SER) has become an important research focus to develop intelligent spoken interfaces. However, most studies predict emotions at the utterance level, ignoring the conversational context, along with the emotional flow and speaker interactions it carries. In this paper, we introduce ACERT...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Experimental Characterization of the Passive Mechanical Behavior of Rat Pelvic Floor Muscles: Effects of Test Conditions and PregnancyExperimental Characterization of the Passive Mechanical Behavior of Rat Pelvic Floor Muscles: Effects of Test Conditions and Pregnancy
Purpose: Pelvic floor muscles undergo large deformations during vaginal delivery, yet the passive tensile behavior of pregnant and non-pregnant pelvic floor muscle and the influence of testing protocols remain incompletely characterized. This study evaluated how pregnancy, loading rate, preconditioning, and storage affect passive tensile mechanics of rat pelvic floor muscle. Methods: Levator ani samples from pregnant and...Purpose: Pelvic floor muscles undergo large deformations during vaginal delivery, yet the passive tensile behavior of pregnant and non-pregnant pelvic floor muscle and the influence of testing protocols remain incompletely characterized. This study evaluated how pregnancy, loading rate, preconditioning, and storage affect passive tensile mechanics of rat pelvic floor muscle. Methods: Levator ani samples from pregnant and...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
LLM-based Conversational AI Knowledge Assistant for MyBuddy Humanoid RobotLLM-based Conversational AI Knowledge Assistant for MyBuddy Humanoid Robot
Humanoid robots are increasingly being popular and developed for human-centered applications, yet their ability to provide intelligent conversations and natural interactive knowledge assistance remains constrained by traditional rule-based dialogue systems, pre-defined responses and limited knowledge repositories. Large language models (LLMs) have emerged as a powerful foundation for enabling natural, adaptive, and...Humanoid robots are increasingly being popular and developed for human-centered applications, yet their ability to provide intelligent conversations and natural interactive knowledge assistance remains constrained by traditional rule-based dialogue systems, pre-defined responses and limited knowledge repositories. Large language models (LLMs) have emerged as a powerful foundation for enabling natural, adaptive, and...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品
阅读建议 核对延迟、硬件条件、功耗和交互任务，再评估能否迁移到现有设备。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
实验室主页发布：sxhfut.github.ioMAC-Lab Official Website Released
实验室主页 sxhfut.github.io 正式发布，集中呈现研究方向、行业方案、学术影响、实验室新闻、前沿分享、媒体关注、团队培养与合作入口。The new bilingual MAC-Lab website presents research directions, industry solutions, academic impact, lab news, frontier sharing, media coverage, student training, and collaboration channels.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 科研复现、开发工具与资源管理。匹配：科研与开发提效、跨学科与产业转化
阅读建议 先核对许可、依赖与复现条件；若适用，用隔离的小任务验证时间和资源收益。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
面部表情识别自适应样本挖掘研究发表于 IEEE Transactions on Fuzzy SystemsAdaptive Sample Mining for Facial Expression Recognition Published in IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems 论文研究面向面部表情识别的模糊隶属度驱动自适应样本挖掘，补强团队多模态情感感知方向的高水平成果链条。The IEEE Transactions on Fuzzy Systems paper studies fuzzy membership-driven adaptive sample mining for facial expression recognition, adding another high-level venue to the lab's multimodal affective perception line.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
普适场景多模态情感计算与干预技术获国际发明展银奖Multimodal Affective Computing and Intervention Technology Wins Silver Award
实验室“普适场景中的多模态情感计算与干预技术”在第十一届国际发明展览会·“一带一路”暨金砖国家技能发展与技术创新大赛中获得银奖。MAC-Lab's multimodal affective computing and intervention technology for ubiquitous scenarios won a silver award at the 11th International Exhibition of Inventions and BRICS skills-development and technology-innovation competition.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、智能体与团队能力
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
实验室参编健康住区环境保障智能系统设计技术导则Lab Contributes to a Group Standard for Healthy Residential Environments
实验室普适场景人因情感计算技术应用于健康住区环境身心表征与保障，参与编写相关团体标准。The lab's human-factor affective computing technology entered standardization work for intelligent systems supporting healthy residential environments.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知、跨学科与产业转化
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
语音情绪识别时频状态空间对偶方法发表于 ICASSP 2025Temporal-Frequency State Space Duality Published at ICASSP 2025
ICASSP 2025 论文提出面向语音情绪识别的高效时频状态空间范式，支撑实验室多模态情感计算的基础能力建设。The ICASSP 2025 paper introduces an efficient temporal-frequency state-space paradigm for speech emotion recognition, aligning with the lab's multimodal affective computing foundation.
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
DEFormer 低光图像与暗视觉增强研究发表于 ICASSP 2025DEFormer Published at ICASSP 2025
DEFormer 研究面向低光图像与暗视觉的 DCT 驱动增强 Transformer，扩展实验室多模态 AI 与可部署感知工具箱。DEFormer studies DCT-driven enhancement transformers for low-light image and dark vision, expanding the lab's multimodal AI and deployable perception toolbox.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Google DeepMind’s New Resident Philosopher Tackles AI EthicsGoogle DeepMind’s New Resident Philosopher Tackles AI Ethics
How should humans relate to generative AI ? In what ways do we, or should we, treat a large language model (LLM) as if it were a person? If an AI became conscious, how could we tell? Does it make sense to think AI could someday have moral rights? These are among the cognitive and ethical questions that occupied philosopher Henry Shevlin at Cambridge...How should humans relate to generative AI ? In what ways do we, or should we, treat a large language model (LLM) as if it were a person? If an AI became conscious, how could we tell? Does it make sense to think AI could someday have moral rights? These are among the cognitive and ethical questions that occupied philosopher Henry Shevlin at Cambridge...
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 心智建模、共情交互与人因工程。匹配：心智与人机交互
阅读建议 核对研究对象、观测窗口和适用条件，选一个可检验的问题用于组会讨论。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Roundtables: A Conversation With the Creator of AI-Designed VirusesRoundtables: A Conversation With the Creator of AI-Designed Viruses
Listen to the session or watch below Can AI design new life forms? In 2025, Stanford University PhD student Samuel King came up with a preliminary answer when he used a generative AI model to propose genetic blueprints for microscopic viruses. It isn’t yet an example of AI-generated life, but that could be next. Watch…Listen to the session or watch below Can AI design new life forms? In 2025, Stanford University PhD student Samuel King came up with a preliminary answer when he used a generative AI model to propose genetic blueprints for microscopic viruses. It isn’t yet an example of AI-generated life, but that could be next. Watch…
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Simulation App Speeds Up Electric Truck Battery DesignSimulation App Speeds Up Electric Truck Battery Design
This article is brought to you by COMSOL . These days, no one blinks an eye at two-day, one-day, and even same-day package deliveries. Despite the plethora of localized fulfillment and distributi on centers that have cropped up to meet the demand, delivery trucks still need to make considerably long drives, often over highways. To reduce fuel and...This article is brought to you by COMSOL . These days, no one blinks an eye at two-day, one-day, and even same-day package deliveries. Despite the plethora of localized fulfillment and distributi on centers that have cropped up to meet the demand, delivery trucks still need to make considerably long drives, often over highways. To reduce fuel and...
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Video Friday: Robot Decommissioning Takes a Fun TurnVideo Friday: Robot Decommissioning Takes a Fun Turn
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. CoRL 2026 : 9–12 November 2026, AUSTIN Humanoids 2026 : 6–9 December 2026, SANTA CLARA, CA Enjoy today’s videos!...Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. CoRL 2026 : 9–12 November 2026, AUSTIN Humanoids 2026 : 6–9 December 2026, SANTA CLARA, CA Enjoy today’s videos!...
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 具身情感交互与端侧部署。匹配：具身与端侧产品
阅读建议 核对延迟、硬件条件、功耗和交互任务，再评估能否迁移到现有设备。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Unlocking Earth AI’s planetary geospatial foundation models for global public healthUnlocking Earth AI’s planetary geospatial foundation models for global public health
来自 Google Research 公开订阅源，内容与 AI Research 及应用型 AI 系统建设相关。Selected from Google Research's public feed for its relevance to AI Research and applied AI systems.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 跨学科方法与产品落地。匹配：跨学科与产业转化
阅读建议 找到可迁移的方法或真实需求，并记录与当前技术路线的差异。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
MIT announces the MIT for America initiative, to strengthen STEM education across the countryMIT announces the MIT for America initiative, to strengthen STEM education across the country
The effort aims to help U.S. learners from kindergarten to community college, with an emphasis on math, making, and the constructive use of AI.The effort aims to help U.S. learners from kindergarten to community college, with an emphasis on math, making, and the constructive use of AI.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 跨学科方法与产品落地。匹配：跨学科与产业转化
阅读建议 找到可迁移的方法或真实需求，并记录与当前技术路线的差异。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Humans in the Loop—Or Just "Meat Tools" for AI Agents? - IEEE SpectrumHumans in the Loop—Or Just "Meat Tools" for AI Agents? - IEEE Spectrum
Humans in the Loop—Or Just "Meat Tools" for AI Agents? IEEE SpectrumHumans in the Loop—Or Just "Meat Tools" for AI Agents? IEEE Spectrum
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 智能体运行时与团队知识积累。匹配：智能体与团队能力
阅读建议 检查记忆、工具调用和失败恢复机制，再决定是否安排最小复现。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Beyond Risk Prediction: Evidence Grounding and Psychosocial Factor Verification for Explainable Suicide Risk AssessmentBeyond Risk Prediction: Evidence Grounding and Psychosocial Factor Verification for Explainable Suicide Risk Assessment
Identifying suicide risk from social networking services (SNS) posts is important for detecting suicide-related signals in online environments. However, risk classification alone provides limited insight into the textual evidence and psychosocial factors behind a prediction. Based on the IEEE BigData 2026 Explainable Suicide Risk Detection Challenge, this study presents a framework consisting of Risk Assessment, Evidence...Identifying suicide risk from social networking services (SNS) posts is important for detecting suicide-related signals in online environments. However, risk classification alone provides limited insight into the textual evidence and psychosocial factors behind a prediction. Based on the IEEE BigData 2026 Explainable Suicide Risk Detection Challenge, this study presents a framework consisting of Risk Assessment, Evidence...
预印本摘要 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Introducing Quine: An AI research system designed for the complexity of biologyIntroducing Quine: An AI research system designed for the complexity of biology
Biology doesn't operate in silos, and neither should the AI representation of it. Quine is an early-stage research effort to create a multimodal world model of biology. By connecting insights across biological scales and modalities, Quine helps scientists computationally search a space far larger than intuition allows and prioritize hypotheses before they...Biology doesn't operate in silos, and neither should the AI representation of it. Quine is an early-stage research effort to create a multimodal world model of biology. By connecting insights across biological scales and modalities, Quine helps scientists computationally search a space far larger than intuition allows and prioritize hypotheses before they...
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
情感计算市场规模、行业份额、预测，2034 年 - Fortune Business Insights情感计算市场规模、行业份额、预测，2034 年 - Fortune Business Insights
情感计算市场规模、行业份额、预测，2034 年 Fortune Business Insights情感计算市场规模、行业份额、预测，2034 年 Fortune Business Insights
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 情感理解与多模态感知。匹配：情感与多模态感知
阅读建议 检查任务、数据切分与基线，判断是否适合加入现有感知评测。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Suki and MedStar Health’s National Center for Human Factors in Healthcare Partner to Pioneer the Science of Ambient AI Adoption | Newswise - NewswiseSuki and MedStar Health’s National Center for Human Factors in Healthcare Partner to Pioneer the Science of Ambient AI Adoption | Newswise - Newswise
Suki and MedStar Health’s National Center for Human Factors in Healthcare Partner to Pioneer the Science of Ambient AI Adoption | Newswise NewswiseSuki and MedStar Health’s National Center for Human Factors in Healthcare Partner to Pioneer the Science of Ambient AI Adoption | Newswise Newswise
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 跨学科方法与产品落地。匹配：跨学科与产业转化
阅读建议 找到可迁移的方法或真实需求，并记录与当前技术路线的差异。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
扩散增强多轮对话潜在背景建模研究发表于 IEEE Transactions on Artificial IntelligenceModeling Latent Background Information in Multiturn Dialogues Using Diffusion Model Published in IEEE Transactions on Artificial Intelligence
孙晓教授团队合作论文于 2026 年 3 月 17 日以 Early Access 形式发表于 IEEE Transactions on Artificial Intelligence，围绕人物、场景、氛围等潜在背景信息建模，提升多轮对话生成合理性。Zishun Cui, Xiao Sun, and Meng Wang published this Early Access article in IEEE Transactions on Artificial Intelligence on 17 March 2026, modeling latent persona, scene, and atmosphere information for more reasonable multi-turn dialogue generation.
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
Padilla lambastes Newsom veto of bill banning AI therapy chatbots - Imperial Valley Press OnlinePadilla lambastes Newsom veto of bill banning AI therapy chatbots - Imperial Valley Press Online
Padilla lambastes Newsom veto of bill banning AI therapy chatbots Imperial Valley Press OnlinePadilla lambastes Newsom veto of bill banning AI therapy chatbots Imperial Valley Press Online
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
AI Therapy Worked for Me. It’s Not for Everyone. - The Free PressAI Therapy Worked for Me. It’s Not for Everyone. - The Free Press
AI Therapy Worked for Me. It’s Not for Everyone. The Free PressAI Therapy Worked for Me. It’s Not for Everyone. The Free Press
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
The Dead Silence of AI Therapy - The AtlanticThe Dead Silence of AI Therapy - The Atlantic
The Dead Silence of AI Therapy The AtlanticThe Dead Silence of AI Therapy The Atlantic
公开来源摘录 · 规则匹配 · 未经模型深度解读
与我们有什么关系 · 怎样用Relevance & next step
关联方向 关注范围之外的新方法或不同观点。保留少量跨领域阅读，避免只看到熟悉观点。
阅读建议 阅读原文，说明它可能改变哪一个已有判断；也可以选择不纳入。
证据边界 上述关联由公开标题和摘录匹配得出，尚未验证效果、复现指标或适用性；不能据此直接作出研究或产品结论。
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2026-10-20 · 10 条精选
对应资料抓取时间 2026-10-20T01:06:19+00:00
- 通过多教师蒸馏框架学习多个互补的语音表示 2026-10-15 · arXiv
- RISHAB-999/Therapiques 2026-10-19 · Recent GitHub
- Timestral: Mistral's time-series foundation models 2026-10-19 · hackernews
- 预印本摘要：提示演化在压力与情绪预测中的策略识别 2026-10-15 · arXiv
- 多模态大语言模型在卡通电影中的社会和情感理解 2026-10-15 · arXiv
- Cross-Dimension and Cross-Modality Relational Tensor Representation Learning for Multimodal Health Data Modeling 2026-10-17 · arXiv
- Advancing coding in low‑resource programming languages 2026-10-19 · RSS · OpenAI News
- Itaú 使用 AI 增强客户和员工互动 2026-10-16 · RSS · OpenAI News
- Alternatives to animal testing are finally taking off 2026-10-19 · hackernews
- Faraday Future和FFR联合发布FF Nova和FF Nova Mini 2026-10-16 · RSS · Google News
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对应资料抓取时间 2026-10-19T04:53:04+00:00
- 通过多教师蒸馏框架学习多个互补的语音表示 2026-10-15 · arXiv
- 预印本摘要：提示演化在压力与情绪预测中的策略识别 2026-10-15 · arXiv
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