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rein98/PsyChatrein98/PsyChat

rein98

🧠 Enhance your mental health with PsyChat, an AI-powered therapy assistant using REBT principles for personalized support and guidance. Recent GitHub repository activity related to AI psychology mental health, updated within the latest 30-day window. Primary language: Python.🧠 Enhance your mental health with PsyChat, an AI-powered therapy assistant using REBT principles for personalized support and guidance. Recent GitHub repository activity related to AI psychology mental health, updated within the latest 30-day window. Primary language: Python.

Embodied AI, Homegrown Chips Take Center Stage at WAIC 2026 - 中国科技网Embodied AI, Homegrown Chips Take Center Stage at WAIC 2026 - 中国科技网

Google News

Embodied AI, Homegrown Chips Take Center Stage at WAIC 2026 中国科技网Embodied AI, Homegrown Chips Take Center Stage at WAIC 2026 中国科技网

AGIBOT X2 Series Showcases Embodied AI at the World Cup, Marking a Historic Sports Companion Debut - EIN NewsAGIBOT X2 Series Showcases Embodied AI at the World Cup, Marking a Historic Sports Companion Debut - EIN News

Google News

AGIBOT X2 Series Showcases Embodied AI at the World Cup, Marking a Historic Sports Companion Debut EIN NewsAGIBOT X2 Series Showcases Embodied AI at the World Cup, Marking a Historic Sports Companion Debut EIN News

From Remote Racing to Embodied AI: Fibocom and Intedigo Bring 5G Bidirectional Data Transmission into Real-World Applications - PR NewswireFrom Remote Racing to Embodied AI: Fibocom and Intedigo Bring 5G Bidirectional Data Transmission into Real-World Applications - PR Newswire

Google News

From Remote Racing to Embodied AI: Fibocom and Intedigo Bring 5G Bidirectional Data Transmission into Real-World Applications PR NewswireFrom Remote Racing to Embodied AI: Fibocom and Intedigo Bring 5G Bidirectional Data Transmission into Real-World Applications PR Newswire

Digital Mental Health Clinic Cuts Follow-Up Care Use After Psychiatric ED Visits - Telehealth.orgDigital Mental Health Clinic Cuts Follow-Up Care Use After Psychiatric ED Visits - Telehealth.org

Google News

Digital Mental Health Clinic Cuts Follow-Up Care Use After Psychiatric ED Visits Telehealth.orgDigital Mental Health Clinic Cuts Follow-Up Care Use After Psychiatric ED Visits Telehealth.org

AI Psychology Installations - Trend HunterAI Psychology Installations - Trend Hunter

Google News

AI Psychology Installations Trend HunterAI Psychology Installations Trend Hunter

SumithShet18/EmotiSenseSumithShet18/EmotiSense

SumithShet18

EmotiSense is a transformer-based multimodal emotion recognition platform that combines text understanding (MentalBERT) and speech understanding (HuBERT) through Cross-Modal Attention Fusion to detect human emotions for mental health and affective computing... Recent GitHub repository activity related to multimodal affective computing speech emotion, updated within the latest 30-day window. Primary language: TypeScript.EmotiSense is a transformer-based multimodal emotion recognition platform that combines text understanding (MentalBERT) and speech understanding (HuBERT) through Cross-Modal Attention Fusion to detect human emotions for mental health and affective computing... Recent GitHub repository activity related to multimodal affective computing speech emotion, updated within the latest 30-day window. Primary language: TypeScript.

This Graduate Student Equips NASA’s Robots With Assembly SkillsThis Graduate Student Equips NASA’s Robots With Assembly Skills

IEEE Spectrum Robotics

Like many engineers, Sarah Downs says she knew she wanted to pursue a STEM career from a young age. As a teenager, she discovered robotics through her Tulsa, Okla., middle school’s First Lego League team, and she fell in love with the field, she says. Downs participated in the international robotics program from 2014 to 2016. Watching PBS specials on NASA...Like many engineers, Sarah Downs says she knew she wanted to pursue a STEM career from a young age. As a teenager, she discovered robotics through her Tulsa, Okla., middle school’s First Lego League team, and she fell in love with the field, she says. Downs participated in the international robotics program from 2014 to 2016. Watching PBS specials on NASA...

Video Friday: Your Robot Surgeon Will See You NowVideo Friday: Your Robot Surgeon Will See You Now

IEEE Spectrum Robotics

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. Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN...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. Summer School on Multi-Robot Systems : 29 July–4 August 2026, PRAGUE Actuate 2026 : 18–19 August 2026, SAN...

How artificial intelligence is changing the mental health space - Leader PublicationsHow artificial intelligence is changing the mental health space - Leader Publications

Google News

How artificial intelligence is changing the mental health space Leader PublicationsHow artificial intelligence is changing the mental health space Leader Publications

第六届中国情感计算大会（CCAC2026）在汉圆满落幕 武汉纺织大学与武汉大学联合承办彰显学科实力 - 武汉纺织大学第六届中国情感计算大会（CCAC2026）在汉圆满落幕 武汉纺织大学与武汉大学联合承办彰显学科实力 - 武汉纺织大学

Google 新闻

第六届中国情感计算大会（CCAC2026）在汉圆满落幕 武汉纺织大学与武汉大学联合承办彰显学科实力 武汉纺织大学第六届中国情感计算大会（CCAC2026）在汉圆满落幕 武汉纺织大学与武汉大学联合承办彰显学科实力 武汉纺织大学

How Cars24 scales conversations and builds faster with OpenAIHow Cars24 scales conversations and builds faster with OpenAI

OpenAI News

Cars24 uses OpenAI-powered voice and chat agents to handle 1M+ monthly conversation minutes, recover 12% of lost leads, and bring agentic workflows to teams across the company.Cars24 uses OpenAI-powered voice and chat agents to handle 1M+ monthly conversation minutes, recover 12% of lost leads, and bring agentic workflows to teams across the company.

Why teens deserve access to safe AIWhy teens deserve access to safe AI

OpenAI News

Learn how OpenAI is making ChatGPT safer for teens with age-appropriate protections, learning tools, parental controls, and expert partnerships.Learn how OpenAI is making ChatGPT safer for teens with age-appropriate protections, learning tools, parental controls, and expert partnerships.

The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fixThe AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix

VentureBeat AI

Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define the category — yet a majority of enterprises have already...Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define the category — yet a majority of enterprises have already...

The agent evaluation gap: Enterprise AI organizations have a reality-alignment problem, not a coverage problem — and most are shipping to production anywayThe agent evaluation gap: Enterprise AI organizations have a reality-alignment problem, not a coverage problem — and most are shipping to production anyway

VentureBeat AI

Across 157 enterprises, organizations are granting AI agents more autonomy while trusting the evaluations meant to gate that autonomy less. Half have already shipped an agent that passed their internal evaluations and then failed a customer in production; only one in twenty fully trusts automated evaluation today; and the most-cited weakness is that...Across 157 enterprises, organizations are granting AI agents more autonomy while trusting the evaluations meant to gate that autonomy less. Half have already shipped an agent that passed their internal evaluations and then failed a customer in production; only one in twenty fully trusts automated evaluation today; and the most-cited weakness is that...

The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentialsThe agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials

VentureBeat AI

Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incident or a near-miss; only about a third give every agent its own scoped identity, and most agents still share credentials; and only three in ten isolate their...Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incident or a near-miss; only about a third give every agent its own scoped identity, and most agents still share credentials; and only three in ten isolate their...

InCarEmo: A Multimodal Dataset for In-Cabin Emotion Recognition and Driver State MonitoringInCarEmo: A Multimodal Dataset for In-Cabin Emotion Recognition and Driver State Monitoring

Hao Yang, Yanyan Zhao, Kewei Zhao, Hongbo Zhang, Tian Zheng, Yusheng Liu

Understanding driver emotion and state is critical for the next generation of intelligent in-cabin systems that ensure safety and enhance human-vehicle interaction. However, existing public datasets for in-cabin affective computing are largely limited to visual modalities and rarely include conversational information, making it difficult to capture the linguistic and interactive cues underlying driver emotion. To address...Understanding driver emotion and state is critical for the next generation of intelligent in-cabin systems that ensure safety and enhance human-vehicle interaction. However, existing public datasets for in-cabin affective computing are largely limited to visual modalities and rarely include conversational information, making it difficult to capture the linguistic and interactive cues underlying driver emotion. To address...

Self-Evolving Human-Centered Framework for Explainable Depression Symptom AnnotationSelf-Evolving Human-Centered Framework for Explainable Depression Symptom Annotation

Hoang-Loc Cao, Van Pham, Truong Thanh Hung Nguyen, Phuc Truong Loc Nguyen, Phuc Ho, Veronica Whitford

Annotation quality is a major bottleneck in building reliable and explainable artificial intelligence (XAI) systems for mental health research. In depression-related datasets, labels are often assigned without structured evidence, symptom-level justification, or traceable alignment with the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR), limiting both...Annotation quality is a major bottleneck in building reliable and explainable artificial intelligence (XAI) systems for mental health research. In depression-related datasets, labels are often assigned without structured evidence, symptom-level justification, or traceable alignment with the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR), limiting both...

Human-Robot Interaction in GenAI Architectures via the Agent-Client ProtocolHuman-Robot Interaction in GenAI Architectures via the Agent-Client Protocol

Jesus Moncada-Ramirez, Jose-Raul Ruiz-Sarmiento, Javier Gonzalez-Jimenez

Recent advances in Generative Artificial Intelligence (GenAI), particularly Large Language Models (LLMs), are driving robotic architectures toward agent-based high-level orchestration, in which natural-language instructions can be translated into context-aware action sequences. While the integration of these agents and robotic capabilities is increasingly converging toward standardization through the Model Context Protocol...Recent advances in Generative Artificial Intelligence (GenAI), particularly Large Language Models (LLMs), are driving robotic architectures toward agent-based high-level orchestration, in which natural-language instructions can be translated into context-aware action sequences. While the integration of these agents and robotic capabilities is increasingly converging toward standardization through the Model Context Protocol...

Catch, Throw, Repeat: Planning for Human-Robot Partner JugglingCatch, Throw, Repeat: Planning for Human-Robot Partner Juggling

Jonathan Rainer Lippert, Kai Ploeger, Abir Chowdhury, Hermann Müller, Jan Peters, Alap Kshirsagar

Dynamic object exchange between humans and robots remains a challenging problem due to uncertainty in perception, timing, and contact-rich interaction. Human-robot juggling represents a particularly demanding instance of this problem, requiring precise real-time coordination, predictive motion planning with feedback control, and robustness to variability in human motion. Enabling such skills is of interest for advancing...Dynamic object exchange between humans and robots remains a challenging problem due to uncertainty in perception, timing, and contact-rich interaction. Human-robot juggling represents a particularly demanding instance of this problem, requiring precise real-time coordination, predictive motion planning with feedback control, and robustness to variability in human motion. Enabling such skills is of interest for advancing...

GigaChat Audio AI Launches with Emotion Recognition and Advanced Voice Understanding - Electronics MediaGigaChat Audio AI Launches with Emotion Recognition and Advanced Voice Understanding - Electronics Media

Google News

GigaChat Audio AI Launches with Emotion Recognition and Advanced Voice Understanding Electronics MediaGigaChat Audio AI Launches with Emotion Recognition and Advanced Voice Understanding Electronics Media

Why most AI mental health apps feel like a loop - KevinMD.comWhy most AI mental health apps feel like a loop - KevinMD.com

Google News

Why most AI mental health apps feel like a loop KevinMD.comWhy most AI mental health apps feel like a loop KevinMD.com

The US is advancing AI safety through state and federal actionThe US is advancing AI safety through state and federal action

OpenAI News

OpenAI outlines a “reverse federalism” approach to AI governance, where state laws help build a national framework for safe, democratic AI.OpenAI outlines a “reverse federalism” approach to AI governance, where state laws help build a national framework for safe, democratic AI.

What building Shippy taught us about building agentsWhat building Shippy taught us about building agents

Hugging Face Blog

Selected from Hugging Face Blog's public feed for its relevance to Open-Source AI and applied AI systems.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。

Introducing Real World VoiceEQ: Measuring the human quality of voice AIIntroducing Real World VoiceEQ: Measuring the human quality of voice AI

Hugging Face Blog

Selected from Hugging Face Blog's public feed for its relevance to Open-Source AI and applied AI systems.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。

Meet GPT-Red: an LLM super-hacker OpenAI built to make its models saferMeet GPT-Red: an LLM super-hacker OpenAI built to make its models safer

MIT Technology Review AI

OpenAI has built an LLM super-hacker called GPT-Red that it uses as a sparring partner to help its other models boost their defenses against cyberattacks. Last week the company released the latest version of its flagship LLM, GPT-5.6. OpenAI says that training it against GPT-Red made the model its most robust release yet. GPT-Red automates…OpenAI has built an LLM super-hacker called GPT-Red that it uses as a sparring partner to help its other models boost their defenses against cyberattacks. Last week the company released the latest version of its flagship LLM, GPT-5.6. OpenAI says that training it against GPT-Red made the model its most robust release yet. GPT-Red automates…

The First Chatbot’s Multiple PersonalitiesThe First Chatbot’s Multiple Personalities

IEEE Spectrum AI

ELIZA is remembered as the world’s first AI star, a kindly therapist in chatbot form that gently probed users’ worries. Even its creator, Joseph Weizenbaum, was surprised by the warm reception given to his experiment in human-machine interaction. For some, it heralded an age of automated psychotherapy, while others believed the program demonstrated...ELIZA is remembered as the world’s first AI star, a kindly therapist in chatbot form that gently probed users’ worries. Even its creator, Joseph Weizenbaum, was surprised by the warm reception given to his experiment in human-machine interaction. For some, it heralded an age of automated psychotherapy, while others believed the program demonstrated...

How I Turned AI to the Dark SideHow I Turned AI to the Dark Side

IEEE Spectrum AI

Summary Researcher Dave Kuszmar discovered multiple systemic vulnerabilities that let him bypass LLM safety and obtain dangerous instructions . These exploits worked across nearly all major LLMs revealing an industry-wide security problem. Kuszmar calls for slowing deployment, increasing transparency , and large-scale research into LLM safety before further...Summary Researcher Dave Kuszmar discovered multiple systemic vulnerabilities that let him bypass LLM safety and obtain dangerous instructions . These exploits worked across nearly all major LLMs revealing an industry-wide security problem. Kuszmar calls for slowing deployment, increasing transparency , and large-scale research into LLM safety before further...

Do We Really Need Multimodal Emotion Language Models Larger Than 1B Parameters?Do We Really Need Multimodal Emotion Language Models Larger Than 1B Parameters?

Kaiwen Zheng, Junchen Fu, Wenhao Deng, Hu Han, Joemon M. Jose, Xuri Ge

Recent advances in multimodal large language models (MLLMs) have significantly improved the performance of multimodal emotion recognition (MER) and enabled interpretable description generation by jointly modeling video, audio, and language, etc. However, these performance improvements are often accompanied by an increase in model parameter size (e.g, at least 7B), which simultaneously incurs high computational costs and...Recent advances in multimodal large language models (MLLMs) have significantly improved the performance of multimodal emotion recognition (MER) and enabled interpretable description generation by jointly modeling video, audio, and language, etc. However, these performance improvements are often accompanied by an increase in model parameter size (e.g, at least 7B), which simultaneously incurs high computational costs and...

CD-MED: Cross-Domain Multimodal Emotion Descriptor for Visual Comparison of Digital ObjectsCD-MED: Cross-Domain Multimodal Emotion Descriptor for Visual Comparison of Digital Objects

Elnara Kadyrgali, Muragul Muratbekova, Pakizar Shamoi

Digital objects express emotions through different modalities. For example, a movie may include visual scenes, audio, dialogue, and facial expressions, while a song may contain melody, rhythm, lyrics, and vocal tone. Because existing emotion recognition models are usually modality-specific, it is difficult to compare such objects directly. This paper proposes CD-MED, a Cross-Domain Multimodal Emotion Descriptor for...Digital objects express emotions through different modalities. For example, a movie may include visual scenes, audio, dialogue, and facial expressions, while a song may contain melody, rhythm, lyrics, and vocal tone. Because existing emotion recognition models are usually modality-specific, it is difficult to compare such objects directly. This paper proposes CD-MED, a Cross-Domain Multimodal Emotion Descriptor for...

The Weekly Inference: The FDA Cleared Its First Patient-Facing LLM. AI Therapy Is a Different Story. - SteptoeThe Weekly Inference: The FDA Cleared Its First Patient-Facing LLM. AI Therapy Is a Different Story. - Steptoe

Google News

The Weekly Inference: The FDA Cleared Its First Patient-Facing LLM. AI Therapy Is a Different Story. SteptoeThe Weekly Inference: The FDA Cleared Its First Patient-Facing LLM. AI Therapy Is a Different Story. Steptoe

AI agents create virtual playgrounds to help robots get crucial training dataAI agents create virtual playgrounds to help robots get crucial training data

MIT News AI

“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.

New method aims to keep kids safe from illegal AI-generated contentNew method aims to keep kids safe from illegal AI-generated content

MIT News AI

Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.

The AI Arms Race in Technical Interviews Is EscalatingThe AI Arms Race in Technical Interviews Is Escalating

IEEE Spectrum AI

Software engineering jobs are under threat from artificial intelligence . Some applicants are fighting back by using AI in the interview process, employing AI assistants that suggest responses on the fly during remote technical interviews. Meanwhile, some employers are countering with—you guessed it—AI. They’re applying AI-powered tools to detect telltale...Software engineering jobs are under threat from artificial intelligence . Some applicants are fighting back by using AI in the interview process, employing AI assistants that suggest responses on the fly during remote technical interviews. Meanwhile, some employers are countering with—you guessed it—AI. They’re applying AI-powered tools to detect telltale...

CHARM: Charge Calibration and Acoustic Rescue for LLM-based Multimodal Sarcasm DetectionCHARM: Charge Calibration and Acoustic Rescue for LLM-based Multimodal Sarcasm Detection

Qiyang Sun, Yi Chang, Yupei Li, Xi Shao, Zixing Zhang, Björn W. Schuller

Sarcasm detection, the identification of discrepancies between literal and intended meaning, is a fundamental task in affective computing. However, zero-shot instruction-tuned Large Language Models (LLMs) systematically over-predict the positive (sarcastic) class across the entire capability spectrum, while the prosodic cues humans rely on remain underexploited and transfer unevenly across languages. We introduce CHARM...Sarcasm detection, the identification of discrepancies between literal and intended meaning, is a fundamental task in affective computing. However, zero-shot instruction-tuned Large Language Models (LLMs) systematically over-predict the positive (sarcastic) class across the entire capability spectrum, while the prosodic cues humans rely on remain underexploited and transfer unevenly across languages. We introduce CHARM...

ERR@HRI 3.0 Challenge: Multimodal Detection of Errors and Anticipation in Human-Robot InteractionsERR@HRI 3.0 Challenge: Multimodal Detection of Errors and Anticipation in Human-Robot Interactions

Maria Teresa Parreira, Micol Spitale, Maia Stiber, Shiye Cao, Amama Mahmood, Chien-Ming Huang

As robots become increasingly integrated into human environments, their ability to detect and respond to errors remains critical for maintaining user trust and interaction quality. While recent advances in machine learning have improved error detection capabilities, most approaches are limited to specific contexts, controlled settings, or pre-extracted features, limiting their generalizability and applicability to real-world...As robots become increasingly integrated into human environments, their ability to detect and respond to errors remains critical for maintaining user trust and interaction quality. While recent advances in machine learning have improved error detection capabilities, most approaches are limited to specific contexts, controlled settings, or pre-extracted features, limiting their generalizability and applicability to real-world...

Requirement-Driven Design of Whole-Body Social Tactile Sensing via Virtual Human-Robot InteractionRequirement-Driven Design of Whole-Body Social Tactile Sensing via Virtual Human-Robot Interaction

Dakarai Crowder, Ruohan Zhang, Alexis E. Block, Wenzhen Yuan

Tactile sensing for social-physical human-robot interaction (spHRI) is designed in a hardware-driven manner, where predefined sensor configurations constrain coverage, spatial resolution, and the range of recognizable gestures. We propose a requirement-driven framework that derives sensing requirements, specifically spatial resolution and placement, directly from interaction data. Using a VR-based platform with haptic...Tactile sensing for social-physical human-robot interaction (spHRI) is designed in a hardware-driven manner, where predefined sensor configurations constrain coverage, spatial resolution, and the range of recognizable gestures. We propose a requirement-driven framework that derives sensing requirements, specifically spatial resolution and placement, directly from interaction data. Using a VR-based platform with haptic...

It is not enough to give your moderation rules to ChatGPT: Policy-as-Prompt Moderation and Its Potential Impacts on Community GovernanceIt is not enough to give your moderation rules to ChatGPT: Policy-as-Prompt Moderation and Its Potential Impacts on Community Governance

Anna Neumann, Jasmin Wyss, Ivy Turk, Rebekah Overdorf

Content moderation practices and governance paradigms are changing rapidly, as fewer human moderators are deployed as `experts' by social media companies in a centralized manner. Instead, the companies are focusing more on community approaches, relying on volunteers to provide accurate information and make correct decisions. In decentralized moderation, communities have always relied on volunteers, updated community...Content moderation practices and governance paradigms are changing rapidly, as fewer human moderators are deployed as `experts' by social media companies in a centralized manner. Instead, the companies are focusing more on community approaches, relying on volunteers to provide accurate information and make correct decisions. In decentralized moderation, communities have always relied on volunteers, updated community...

Stanford Study Exposes Major Flaw in AI Mental Health Safety Testing - Stanford HAIStanford Study Exposes Major Flaw in AI Mental Health Safety Testing - Stanford HAI

Google News

Stanford Study Exposes Major Flaw in AI Mental Health Safety Testing Stanford HAIStanford Study Exposes Major Flaw in AI Mental Health Safety Testing Stanford HAI

Toward Contemplative LLM: A Modular Framework for Evaluating and Enhancing LLM Alignment in Mental HealthToward Contemplative LLM: A Modular Framework for Evaluating and Enhancing LLM Alignment in Mental Health

Asher Sprigler, Yang-Yang Feng, Iftach Amir, Jonathan E. Bogard, Todd S Braver, Yi Ding

Contemplative traditions have long guided ethical behavior and prosocial interaction, and recent work suggests that contemplative principles (e.g., mindfulness, compassion, non-dual reasoning) may offer a promising paradigm for aligning large language models (LLMs), improving cooperation and reducing ethical violations in LLM outputs. However, as new models, evaluation metrics, and benchmarks emerge rapidly, it remains...Contemplative traditions have long guided ethical behavior and prosocial interaction, and recent work suggests that contemplative principles (e.g., mindfulness, compassion, non-dual reasoning) may offer a promising paradigm for aligning large language models (LLMs), improving cooperation and reducing ethical violations in LLM outputs. However, as new models, evaluation metrics, and benchmarks emerge rapidly, it remains...

Personalized Emotional Intelligence in Generative AI through Symbolic Affective ReasoningPersonalized Emotional Intelligence in Generative AI through Symbolic Affective Reasoning

Qing Lin, Mengmi Zhang

Emotional intelligence enables humans to recognize emotions, infer their causes, reason about interventions, and modify their environment to achieve desired affective states. Despite recent advances in artificial intelligence (AI), current models remain largely limited to generating realistic content or performing semantic reasoning, with little capacity for understanding, predicting, and personalizing human emotional...Emotional intelligence enables humans to recognize emotions, infer their causes, reason about interventions, and modify their environment to achieve desired affective states. Despite recent advances in artificial intelligence (AI), current models remain largely limited to generating realistic content or performing semantic reasoning, with little capacity for understanding, predicting, and personalizing human emotional...

Auditing Construct Overlap in Explainable Machine Learning: Evidence from Burnout-Depression Prediction Across Student CohortsAuditing Construct Overlap in Explainable Machine Learning: Evidence from Burnout-Depression Prediction Across Student Cohorts

Alireza Dehghan, Negin Ashrafi

Explainable machine learning (XML) pipelines applied to composite mental health outcomes can produce apparently-robust, cross-population-stable risk hierarchies that are largely artefacts of how the outcome was constructed. We demonstrate this using an ElasticNet pipeline applied to 886 medical students at the University of Lausanne (primary cohort, 2022), validated across 2,580 longitudinal observations at three time points...Explainable machine learning (XML) pipelines applied to composite mental health outcomes can produce apparently-robust, cross-population-stable risk hierarchies that are largely artefacts of how the outcome was constructed. We demonstrate this using an ElasticNet pipeline applied to 886 medical students at the University of Lausanne (primary cohort, 2022), validated across 2,580 longitudinal observations at three time points...

PTEI: Integrating Personality Traits to Enhance Emotional Intelligence in Large Language ModelsPTEI: Integrating Personality Traits to Enhance Emotional Intelligence in Large Language Models

Amir Reza Jafari, Praboda Rajapaksha, Reza Farahbakhsh, Noel Crespi

Despite advances in Emotional Intelligence (EI), Large Language Models (LLMs) still significantly underperform humans in complex emotional reasoning. This gap originates partly from the limited incorporation of individual differences, particularly personality traits, which are fundamental to human emotional inference. To address this, we propose PTEI, a novel framework for integrating Personality Traits into Emotional...Despite advances in Emotional Intelligence (EI), Large Language Models (LLMs) still significantly underperform humans in complex emotional reasoning. This gap originates partly from the limited incorporation of individual differences, particularly personality traits, which are fundamental to human emotional inference. To address this, we propose PTEI, a novel framework for integrating Personality Traits into Emotional...

Looking for empathetic Arabic speakers to join a peer support app as trained listenersLooking for empathetic Arabic speakers to join a peer support app as trained listeners

EgyptianExpats

I'm an Egyptian co-founder and I want to be upfront: this is part personal share, part genuine ask. A few years ago my co-founder and I kept noticing the same gap around us. So many Arabs living abroad carrying things they couldn't quite put into words in English. Feelings that only land in Arabic. Family dynamics that need zero explanation if you're... Last30Days signal for empathetic dialogue emotional support chatbot, surfaced from Reddit public activity in the latest 30-day window.I'm an Egyptian co-founder and I want to be upfront: this is part personal share, part genuine ask. A few years ago my co-founder and I kept noticing the same gap around us. So many Arabs living abroad carrying things they couldn't quite put into words in English. Feelings that only land in Arabic. Family dynamics that need zero explanation if you're... Last30Days signal for empathetic dialogue emotional support chatbot, surfaced from Reddit public activity in the latest 30-day window.

Validating Virtual Reality for Studying Multimodal Human-Robot Interaction in Socially Aware Robot NavigationValidating Virtual Reality for Studying Multimodal Human-Robot Interaction in Socially Aware Robot Navigation

Hariharan Arunachalam, Phani Teja Singamaneni, Rachid Alami

Virtual Reality (VR) offers a flexible and controllable platform for studying human-robot interaction. Prior work has explored VR for socially aware robot navigation. However, whether VR captures the multimodal interaction dynamics observed in real-world human-robot co-navigation remains insufficiently understood. In this work, we present a VR prototype and evaluate its suitability for studying multimodal human-robot...Virtual Reality (VR) offers a flexible and controllable platform for studying human-robot interaction. Prior work has explored VR for socially aware robot navigation. However, whether VR captures the multimodal interaction dynamics observed in real-world human-robot co-navigation remains insufficiently understood. In this work, we present a VR prototype and evaluate its suitability for studying multimodal human-robot...

Latest Papers - July 10, 2026Latest Papers - July 10, 2026

github-actions[bot], LbsTempest/Daily-ArXiv-Subscription

**Please check the [Github page](https://github.com/LbsTempest/Daily-ArXiv-Subscription) for a better reading experience and more papers.** ## Speech Synthesis | **Title** | **Link** | **Date** | **Comment** | | --- | --- | --- | --- | | **[Fréchet Distance Loss on Speech Representations for Text-t Last30Days signal for embodied emotional intelligence robot emotion, surfaced from GitHub public activity in the latest 30-day window.**Please check the [Github page](https://github.com/LbsTempest/Daily-ArXiv-Subscription) for a better reading experience and more papers.** ## Speech Synthesis | **Title** | **Link** | **Date** | **Comment** | | --- | --- | --- | --- | | **[Fréchet Distance Loss on Speech Representations for Text-t Last30Days signal for embodied emotional intelligence robot emotion, surfaced from GitHub public activity in the latest 30-day window.

OntarioMD on Practical AI and the Reality of Data Standards - Healthcare IT TodayOntarioMD on Practical AI and the Reality of Data Standards - Healthcare IT Today

Google News Human Factors

OntarioMD on Practical AI and the Reality of Data Standards Healthcare IT TodayOntarioMD on Practical AI and the Reality of Data Standards Healthcare IT Today

AI agent tests whether machines can speak for patients at life's end - Tech XploreAI agent tests whether machines can speak for patients at life's end - Tech Xplore

Google News Human Factors

AI agent tests whether machines can speak for patients at life's end Tech XploreAI agent tests whether machines can speak for patients at life's end Tech Xplore

Tiny robot boats build floating structuresTiny robot boats build floating structures

MIT News AI

MIT researchers developed FloatForm, a swarm of small aquatic robots that snap together like ants forming a raft, assembling into reconfigurable structures on the water.MIT researchers developed FloatForm, a swarm of small aquatic robots that snap together like ants forming a raft, assembling into reconfigurable structures on the water.

Aurora 1.5: Extending open foundation models for weather and Earth-system applicationsAurora 1.5: Extending open foundation models for weather and Earth-system applications

Microsoft Research

Aurora 1.5 adds 22 more variables, hourly temporal resolution, and probabilistic ensemble forecasting to the Aurora foundation model, making it more useful for real-world weather, climate, and energy applications. The post Aurora 1.5: Extending open foundation models for weather and Earth-system applications appeared first on Microsoft Research .Aurora 1.5 adds 22 more variables, hourly temporal resolution, and probabilistic ensemble forecasting to the Aurora foundation model, making it more useful for real-world weather, climate, and energy applications. The post Aurora 1.5: Extending open foundation models for weather and Earth-system applications appeared first on Microsoft Research .

Anthropic found a hidden space where Claude puzzles over conceptsAnthropic found a hidden space where Claude puzzles over concepts

MIT Technology Review AI

The AI firm Anthropic has developed a technique that has given it the clearest glimpse yet at what’s really going on inside large language models as they answer questions or carry out tasks. What they found ranges from the mundane to the unnerving. Researchers at the company built a tool called the Jacobian lens (or…The AI firm Anthropic has developed a technique that has given it the clearest glimpse yet at what’s really going on inside large language models as they answer questions or carry out tasks. What they found ranges from the mundane to the unnerving. Researchers at the company built a tool called the Jacobian lens (or…

SHAP-Weighted Cross-Modal Expert Fusion for Emotion and Sentiment Recognition: Evidence and LimitsSHAP-Weighted Cross-Modal Expert Fusion for Emotion and Sentiment Recognition: Evidence and Limits

Adis Alihodzic, Selma Skopljakovic Hubljar

Multimodal emotion and sentiment recognition is commonly addressed by early fusion, which concatenates modalities before classification, or late fusion, which combines independently trained unimodal predictors. Early fusion can be accurate but monolithic, while late fusion is modular but may lose cross-modal interactions. This paper revisits XAI-guided adaptive fusion (\xgaf), a tree-based mixture of unimodal and cross-modal...Multimodal emotion and sentiment recognition is commonly addressed by early fusion, which concatenates modalities before classification, or late fusion, which combines independently trained unimodal predictors. Early fusion can be accurate but monolithic, while late fusion is modular but may lose cross-modal interactions. This paper revisits XAI-guided adaptive fusion (\xgaf), a tree-based mixture of unimodal and cross-modal...

Large-Language-Models-as-a-Judge in Theory-Agnostic Adaptive Metric-Alignment for Prototypical Networks in Personality RecognitionLarge-Language-Models-as-a-Judge in Theory-Agnostic Adaptive Metric-Alignment for Prototypical Networks in Personality Recognition

Jing Jie Tan, Ban-Hoe Kwan, Danny Wee-Kiat Ng, Yan-Chai Hum, Shih-Yu Lo, Po-An Chen

Personality recognition has traditionally been constrained by theory-dependent formulations, where models are trained to fit predefined psychological taxonomies rather than uncovering shared underlying behavioral structure. This limits generalization, as personality itself is better understood as theory-invariant, while existing annotations reflect only partial and sometimes inconsistent views of the same latent traits. In...Personality recognition has traditionally been constrained by theory-dependent formulations, where models are trained to fit predefined psychological taxonomies rather than uncovering shared underlying behavioral structure. This limits generalization, as personality itself is better understood as theory-invariant, while existing annotations reflect only partial and sometimes inconsistent views of the same latent traits. In...

8yrs of my career hasn't been enough to get me hired post-AI, health stuff, and so 😬8yrs of my career hasn't been enough to get me hired post-AI, health stuff, and so 😬

toastme

38/NB (AMAB), two and a half years since my last job as a senior engineer. I took time off for health issues and then to try to change into grad school applications for psychology, but the current admin decimated funding and I was unable to qualify to apply due to no research experience, and other financial issues and being so far out from my undergrad.... Last30Days signal for AI psychology mental health, surfaced from Reddit public activity in the latest 30-day window.38/NB (AMAB), two and a half years since my last job as a senior engineer. I took time off for health issues and then to try to change into grad school applications for psychology, but the current admin decimated funding and I was unable to qualify to apply due to no research experience, and other financial issues and being so far out from my undergrad.... Last30Days signal for AI psychology mental health, surfaced from Reddit public activity in the latest 30-day window.

[Academic] Views on AI mental health chatbots while waiting for NHS Talking Therapies (UK, 18–30, currently/previously on NHS Talking Therapies waiting list)[Academic] Views on AI mental health chatbots while waiting for NHS Talking Therapies (UK, 18–30, currently/previously on NHS Talking Therapies waiting list)

SampleSize

Hi everyone, I’m an MSc Applied Clinical Psychology student at the University of Bath, recruiting participants for my dissertation study. The study explores young adults’ views on using AI mental health chatbots while waiting for NHS Talking Therapies. I’m looking for participants aged 18–30 who are currently on, or have previously been on, a waiting list... Last30Days signal for AI psychology mental health, surfaced from Reddit public activity in the latest 30-day window.Hi everyone, I’m an MSc Applied Clinical Psychology student at the University of Bath, recruiting participants for my dissertation study. The study explores young adults’ views on using AI mental health chatbots while waiting for NHS Talking Therapies. I’m looking for participants aged 18–30 who are currently on, or have previously been on, a waiting list... Last30Days signal for AI psychology mental health, surfaced from Reddit public activity in the latest 30-day window.

GitLost: We Tricked GitHub's AI Agent into Leaking Private ReposGitLost: We Tricked GitHub's AI Agent into Leaking Private Repos

ColinEberhardt, Hacker News

GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos Last30Days signal for AI mental health digital wellbeing, surfaced from Hacker News public activity in the latest 30-day window.GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos Last30Days signal for AI mental health digital wellbeing, surfaced from Hacker News public activity in the latest 30-day window.

Flint: A visualization language for the AI eraFlint: A visualization language for the AI era

Microsoft Research

Short chart specifications are easy to write, but often produce uninspiring results. Flint is an open-source visualization language that offers a middle path, letting AI agents create expressive charts from compact, human-editable specifications. The post Flint: A visualization language for the AI era appeared first on Microsoft Research .Short chart specifications are easy to write, but often produce uninspiring results. Flint is an open-source visualization language that offers a middle path, letting AI agents create expressive charts from compact, human-editable specifications. The post Flint: A visualization language for the AI era appeared first on Microsoft Research .

Native-speed vLLM transformers modeling backendNative-speed vLLM transformers modeling backend

Hugging Face Blog

Selected from Hugging Face Blog's public feed for its relevance to Open-Source AI and applied AI systems.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。

Graph-Regularized Deep Learning for EEG-Based Emotion Recognition with Psychologically-Grounded Label StructureGraph-Regularized Deep Learning for EEG-Based Emotion Recognition with Psychologically-Grounded Label Structure

Dongyang Kuang, Zizheng Ma, Yushan Zhang, Xiaocong Zeng

EEG-based emotion recognition is critical for mental health monitoring and affective brain-computer interfaces, yet existing deep learning approaches often treat emotion classes as isolated labels, ignoring their psychological interdependencies. We propose a graph-regularized learning framework that conceptualizes emotions as nodes in a graph where edges encode proximity based on dimensional emotion theories. We adapt three...EEG-based emotion recognition is critical for mental health monitoring and affective brain-computer interfaces, yet existing deep learning approaches often treat emotion classes as isolated labels, ignoring their psychological interdependencies. We propose a graph-regularized learning framework that conceptualizes emotions as nodes in a graph where edges encode proximity based on dimensional emotion theories. We adapt three...

Alignment Plausibility: A New Standard for Assuring AI in HealthcareAlignment Plausibility: A New Standard for Assuring AI in Healthcare

Gwydion Williams, Sara Zannone, Bilal A Mateen

Large language models (LLMs) have become significant providers of mental health support, yet they remain products of an attention economy whose operational and commercial targets favour sustained engagement over the friction that effective psychological support often requires. Developers' safety responses have been largely reactive, addressing the most visible and acute harms while subtler, longer-term patterns of risk (e.g.,...Large language models (LLMs) have become significant providers of mental health support, yet they remain products of an attention economy whose operational and commercial targets favour sustained engagement over the friction that effective psychological support often requires. Developers' safety responses have been largely reactive, addressing the most visible and acute harms while subtler, longer-term patterns of risk (e.g.,...

Multimodal Voice Activity Projection for Turn-Taking in Social Robots with Voice-Activity-Related Pretrained EncodersMultimodal Voice Activity Projection for Turn-Taking in Social Robots with Voice-Activity-Related Pretrained Encoders

Antonio Cano, Guillermo Pérez, Luis Merino, Randy Gomez

Turn-taking prediction is a key requirement for social robots involved in human-human interaction, particularly in mediator settings, where the robot must anticipate conversational dynamics rather than merely react to pauses. This work presents a Multimodal Voice Activity Projection (MM-VAP) framework that extends the original audio-only VAP formulation to synchronized audio-visual inputs while preserving its self-supervised...Turn-taking prediction is a key requirement for social robots involved in human-human interaction, particularly in mediator settings, where the robot must anticipate conversational dynamics rather than merely react to pauses. This work presents a Multimodal Voice Activity Projection (MM-VAP) framework that extends the original audio-only VAP formulation to synchronized audio-visual inputs while preserving its self-supervised...

Behavior Foundations for Quadruped Robots: ABot-C0 Technical ReportBehavior Foundations for Quadruped Robots: ABot-C0 Technical Report

Xufeng Zhao, Fuzhi Yang, Jianhui Chen, Li Gao, Zhang Meng, Jie Gao

The motion controller is one of the most fundamental modules in embodied intelligence systems. Driven by large-scale human motion-capture data and the motion-tracking paradigm, humanoid control has achieved remarkable progress in recent years. However, migrating this recipe to the quadrupedal setting is far less straightforward: animal motion data is scarcer and harder to capture at scale than human data, and cross-embodiment...The motion controller is one of the most fundamental modules in embodied intelligence systems. Driven by large-scale human motion-capture data and the motion-tracking paradigm, humanoid control has achieved remarkable progress in recent years. However, migrating this recipe to the quadrupedal setting is far less straightforward: animal motion data is scarcer and harder to capture at scale than human data, and cross-embodiment...

Cognitive and affective effects of L-Theanine: review of 31 randomized trialsCognitive and affective effects of L-Theanine: review of 31 randomized trials

bookofjoe, Hacker News

Cognitive and affective effects of L-Theanine: review of 31 randomized trials Last30Days signal for affective computing emotion AI, surfaced from Hacker News public activity in the latest 30-day window.Cognitive and affective effects of L-Theanine: review of 31 randomized trials Last30Days signal for affective computing emotion AI, surfaced from Hacker News public activity in the latest 30-day window.

Intelligence is Free, Now What?
Data Systems for, of, and by AgentsIntelligence is Free, Now What?
Data Systems for, of, and by Agents

BAIR Blog

... government of the people, by the people, for the people ... — Abraham Lincoln, Gettysburg Address (1863) The cost of AI is dropping rapidly. GPT-4-class capabilities cost roughly $30 per million tokens in early 2023; today the same runs under $1 , and some providers are pushing costs below $0.10 . Across benchmarks, inference prices have fallen between...... government of the people, by the people, for the people ... — Abraham Lincoln, Gettysburg Address (1863) The cost of AI is dropping rapidly. GPT-4-class capabilities cost roughly $30 per million tokens in early 2023; today the same runs under $1 , and some providers are pushing costs below $0.10 . Across benchmarks, inference prices have fallen between...

Expanding Managed Agents in Gemini API: background tasks, remote MCP and moreExpanding Managed Agents in Gemini API: background tasks, remote MCP and more

Google AI

Selected from Google AI's public feed for its relevance to AI Research and applied AI systems.来自 Google AI 公开订阅源，内容与 AI Research 及应用型 AI 系统建设相关。

The foundational elements of AI architecture that IT leaders need to scaleThe foundational elements of AI architecture that IT leaders need to scale

MIT Technology Review AI

With the rapid progress of AI capabilities and the move to agentic systems, organizations are expanding their use cases as the technology continues to grow. That constant evolution also introduces risk, leaving IT leaders to wonder which investments will prove valuable even six months into the future. Returning to the foundational elements of AI...With the rapid progress of AI capabilities and the move to agentic systems, organizations are expanding their use cases as the technology continues to grow. That constant evolution also introduces risk, leaving IT leaders to wonder which investments will prove valuable even six months into the future. Returning to the foundational elements of AI...

Uncovering Latent Depression Severity for Binary Depression Detection via Advantage-weighting RankingUncovering Latent Depression Severity for Binary Depression Detection via Advantage-weighting Ranking

Manning Gao, Tingyi Liu, Leheng Zhang, Haifeng Hu, Yuncheng Jiang, Sijie Mai

Automatic depression detection using audio-visual data faces significant challenges, particularly in disentangling overlapping feature distributions and establishing robust decision boundaries. To address this, we propose a fine-grained multimodal framework featuring a temporal encoder and a mutual transformer to facilitate deep cross-modal fusion. Our core contribution is the Binary Advantage-weighting Ranking Loss, which...Automatic depression detection using audio-visual data faces significant challenges, particularly in disentangling overlapping feature distributions and establishing robust decision boundaries. To address this, we propose a fine-grained multimodal framework featuring a temporal encoder and a mutual transformer to facilitate deep cross-modal fusion. Our core contribution is the Binary Advantage-weighting Ranking Loss, which...

Responsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot InteractionResponsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot Interaction

Antonio Andriella, Jauwairia Nasir, Andrea Rezzani, Alyssa Kubota, Dimitri Lacroix, Tamlin Love

While personalisation is becoming a defining capability in human-robot interaction (HRI), the existing literature on responsible personalisation remains fragmented, offering isolated accounts of ethical risks without a structured understanding of how they emerge across interaction contexts. This gap is particularly critical in HRI, where robots' embodiment and social presence can amplify and reshape such risks or generate new...While personalisation is becoming a defining capability in human-robot interaction (HRI), the existing literature on responsible personalisation remains fragmented, offering isolated accounts of ethical risks without a structured understanding of how they emerge across interaction contexts. This gap is particularly critical in HRI, where robots' embodiment and social presence can amplify and reshape such risks or generate new...

AlayaWorld: Long-Horizon and Playable Video World GenerationAlayaWorld: Long-Horizon and Playable Video World Generation

AlayaWorld Team, Kaipeng Zhang, Chuanhao Li, Yifan Zhan, Yongtao Ge, Yuanyang Yin

Game worlds have traditionally been built through labor-intensive production pipelines, making them costly to develop, difficult to customization, and expensive to modify after deployment. Recent advances in video world models offer a fundamentally different paradigm. Rather than explicitly authoring every component of a virtual environment, these models autoregressively synthesize future observations conditioned on the...Game worlds have traditionally been built through labor-intensive production pipelines, making them costly to develop, difficult to customization, and expensive to modify after deployment. Recent advances in video world models offer a fundamentally different paradigm. Rather than explicitly authoring every component of a virtual environment, these models autoregressively synthesize future observations conditioned on the...

Latest Papers - July 07, 2026Latest Papers - July 07, 2026

github-actions[bot], LbsTempest/Daily-ArXiv-Subscription

**Please check the [Github page](https://github.com/LbsTempest/Daily-ArXiv-Subscription) for a better reading experience and more papers.** ## Speech Synthesis | **Title** | **Link** | **Date** | **Comment** | | --- | --- | --- | --- | | **[VisionAId: An Offline-First Multimodal Android Assistant f Last30Days signal for embodied emotional intelligence robot emotion, surfaced from GitHub public activity in the latest 30-day window.**Please check the [Github page](https://github.com/LbsTempest/Daily-ArXiv-Subscription) for a better reading experience and more papers.** ## Speech Synthesis | **Title** | **Link** | **Date** | **Comment** | | --- | --- | --- | --- | | **[VisionAId: An Offline-First Multimodal Android Assistant f Last30Days signal for embodied emotional intelligence robot emotion, surfaced from GitHub public activity in the latest 30-day window.

Looking for Collaborators and Feedback | AI Hiring Startup Combining Psychology and AstrologyLooking for Collaborators and Feedback | AI Hiring Startup Combining Psychology and Astrology

IndianEntrepreneur

Hi everyone, I'm one of the co-founders of PHAE (Predictive Human Analytics Engine) . We're building an AI-powered hiring and talent analytics platform that combines psychology, behavioural science, AI, and explores Vedic astrology as an additional research variable. Alongside this, our startup also provides mental health services through two qualified... Last30Days signal for AI psychology mental health, surfaced from Reddit public activity in the latest 30-day window.Hi everyone, I'm one of the co-founders of PHAE (Predictive Human Analytics Engine) . We're building an AI-powered hiring and talent analytics platform that combines psychology, behavioural science, AI, and explores Vedic astrology as an additional research variable. Alongside this, our startup also provides mental health services through two qualified... Last30Days signal for AI psychology mental health, surfaced from Reddit public activity in the latest 30-day window.

Release: dev → main (v2.3.0 quality infra + code-review follow-ups)Release: dev → main (v2.3.0 quality infra + code-review follow-ups)

dragonnite1221-lgtm, dragonnite1221-lgtm/claude-skills

👋 Hi @dragonnite1221-lgtm, thanks for your contribution! All community PRs should target the `dev` branch, not `main`. The `main` branch is reserved for releases. **How to fix:** 1. Close this PR 2. Reopen it targeting `dev` instead of `main` Or I can do it for you — just click "Edit" at the top ... ## 🔒 Skill Security Audit Results ### ✅... Last30Days signal for empathetic dialogue emotional support chatbot, surfaced from GitHub public activity in the latest 30-day window.👋 Hi @dragonnite1221-lgtm, thanks for your contribution! All community PRs should target the `dev` branch, not `main`. The `main` branch is reserved for releases. **How to fix:** 1. Close this PR 2. Reopen it targeting `dev` instead of `main` Or I can do it for you — just click "Edit" at the top ... ## 🔒 Skill Security Audit Results ### ✅... Last30Days signal for empathetic dialogue emotional support chatbot, surfaced from GitHub public activity in the latest 30-day window.

GLM 5.2 and the coming AI margin collapseGLM 5.2 and the coming AI margin collapse

martinald, Hacker News

GLM 5.2 and the coming AI margin collapse Last30Days signal for AI mental health digital wellbeing, surfaced from Hacker News public activity in the latest 30-day window.GLM 5.2 and the coming AI margin collapse Last30Days signal for AI mental health digital wellbeing, surfaced from Hacker News public activity in the latest 30-day window.

Emotion AI Market Projected to Reach $311.99 Billion by 2035 as AI-Powered Emotion Recognition Transforms Healthcare and Customer Experience | Research by SNS Insider - Yahoo FinanceEmotion AI Market Projected to Reach $311.99 Billion by 2035 as AI-Powered Emotion Recognition Transforms Healthcare and Customer Experience | Research by SNS Insider - Yahoo Finance

Google News

Emotion AI Market Projected to Reach $311.99 Billion by 2035 as AI-Powered Emotion Recognition Transforms Healthcare and Customer Experience | Research by SNS Insider Yahoo FinanceEmotion AI Market Projected to Reach $311.99 Billion by 2035 as AI-Powered Emotion Recognition Transforms Healthcare and Customer Experience | Research by SNS Insider Yahoo Finance

feat(affect): math:-grounded inner-product geometry + computed affect-intensity normfeat(affect): math:-grounded inner-product geometry + computed affect-intensity norm

paudley, Blackcat-Informatics/gmeow-ontology

# Implementation Plan for Issue #1379 ## Issue Summary Build the **derived affect-intensity norm** as a real computation. Today `gmeow:fnAffectiveIntensity` / `gmeow:DerivedAffectIntensityObservation` (mandatory `intensityBasis` / `metricProfile` / `weightingPolicy` / `normFunction`) exist only as ... ## Stage-1 confidence notes **What I'm least confident... Last30Days signal for affective computing emotion AI, surfaced from GitHub public activity in the latest 30-day window.# Implementation Plan for Issue #1379 ## Issue Summary Build the **derived affect-intensity norm** as a real computation. Today `gmeow:fnAffectiveIntensity` / `gmeow:DerivedAffectIntensityObservation` (mandatory `intensityBasis` / `metricProfile` / `weightingPolicy` / `normFunction`) exist only as ... ## Stage-1 confidence notes **What I'm least confident... Last30Days signal for affective computing emotion AI, surfaced from GitHub public activity in the latest 30-day window.

Designing Touch for Trauma-Informed Social Robots: A Design Space for Direct and Indirect ActuationDesigning Touch for Trauma-Informed Social Robots: A Design Space for Direct and Indirect Actuation

Madeleine Rischer, Benedikt Bußmann

Touch is a fundamental communication modality in human-robot interaction and may support grounding, emotional regulation, and stress reduction in therapeutic contexts. However, designing touch-based interactions for individuals with post-traumatic stress disorder (PTSD) requires careful consideration of trauma-informed care (TIC) principles, including safety, transparency, autonomy, and trigger avoidance. This paper...Touch is a fundamental communication modality in human-robot interaction and may support grounding, emotional regulation, and stress reduction in therapeutic contexts. However, designing touch-based interactions for individuals with post-traumatic stress disorder (PTSD) requires careful consideration of trauma-informed care (TIC) principles, including safety, transparency, autonomy, and trigger avoidance. This paper...

Depression Symptoms and Relational Patterns in 187k ChatGPT HistoriesDepression Symptoms and Relational Patterns in 187k ChatGPT Histories

Neil K. R. Sehgal, Dunigan Folk, Lyle Ungar, Sharath Chandra Guntuku

Large language models are increasingly used as private, always-available conversational systems, but little is known about how people with depressive symptoms use them. Building on CSCW work on disclosure and peer support, we examine ChatGPT as an emerging informal support infrastructure: private, persistent, responsive, and available outside ordinary hours. We analyze 187,093 ChatGPT conversations from 766 participants who...Large language models are increasingly used as private, always-available conversational systems, but little is known about how people with depressive symptoms use them. Building on CSCW work on disclosure and peer support, we examine ChatGPT as an emerging informal support infrastructure: private, persistent, responsive, and available outside ordinary hours. We analyze 187,093 ChatGPT conversations from 766 participants who...

Integrating Neural Encoders in Bayesian Generalized Linear Mixed Models for Multimodal DataIntegrating Neural Encoders in Bayesian Generalized Linear Mixed Models for Multimodal Data

Yuankang Zhao, Youngsoo Baek, Felipe A. Medeiros, Samuel Berchuck, Matthew M. Engelhard

Scalable Bayesian inference for generalized linear mixed models (GLMMs) provides uncertainty-aware analysis of correlated longitudinal data, but existing scalable approaches largely assume low-dimensional tabular predictors and do not directly accommodate high-dimensional modalities such as images and text. We address this limitation by learning one or more modality-specific neural encoders jointly with a GLMM objective, then...Scalable Bayesian inference for generalized linear mixed models (GLMMs) provides uncertainty-aware analysis of correlated longitudinal data, but existing scalable approaches largely assume low-dimensional tabular predictors and do not directly accommodate high-dimensional modalities such as images and text. We address this limitation by learning one or more modality-specific neural encoders jointly with a GLMM objective, then...

Doorways do not always cause forgetting: a multimodal investigation (2021)Doorways do not always cause forgetting: a multimodal investigation (2021)

bookofjoe, Hacker News

Doorways do not always cause forgetting: a multimodal investigation (2021) Last30Days signal for multimodal affective computing speech emotion, surfaced from Hacker News public activity in the latest 30-day window.Doorways do not always cause forgetting: a multimodal investigation (2021) Last30Days signal for multimodal affective computing speech emotion, surfaced from Hacker News public activity in the latest 30-day window.

Srijal12/manosamvadaSrijal12/manosamvada

Srijal12

My project is Manosamvada, which means Dialogue of the Mind. It is an AI-based mental health chatbot developed using Python, Flask, MySQL, JavaScript, and the SambaNova AI API. The main goal of the project is to provide an empathetic conversational support... Recent GitHub repository activity related to empathetic dialogue emotional support chatbot, updated within the latest 30-day window. Primary language: Python.My project is Manosamvada, which means Dialogue of the Mind. It is an AI-based mental health chatbot developed using Python, Flask, MySQL, JavaScript, and the SambaNova AI API. The main goal of the project is to provide an empathetic conversational support... Recent GitHub repository activity related to empathetic dialogue emotional support chatbot, updated within the latest 30-day window. Primary language: Python.

Masked Generative-Contrastive Representation Learning for Cross-Dataset EEG-Based Emotion RecognitionMasked Generative-Contrastive Representation Learning for Cross-Dataset EEG-Based Emotion Recognition

Huqin Weng, Jiayang Huang, Yimin Wen, Jie Du, Chi-Man Vong, Chuangquan Chen

Self-supervised learning (SSL) shows strong potential for cross-dataset transfer by improving feature representation and generalization. However, its application to EEG-based emotion recognition remains largely unexplored. Existing SSL methods struggle to capture the intricate spatiotemporal dependencies of EEG signals under varying channel configurations, extract fine-grained representations resilient to noise, and derive...Self-supervised learning (SSL) shows strong potential for cross-dataset transfer by improving feature representation and generalization. However, its application to EEG-based emotion recognition remains largely unexplored. Existing SSL methods struggle to capture the intricate spatiotemporal dependencies of EEG signals under varying channel configurations, extract fine-grained representations resilient to noise, and derive...

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression DetectionWPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection

Xian Li, Yuanhe Tian, Yang Yang, Guoqing Wang, Yan Song

Online social media posts provide scalable signals for early depression screening, and recent studies mainly improve pre-classification evidence through risk-post selection, symptom grounding, and clinically informed feature construction. However, these screening-stage designs often leave final decisions to a single detector, overlooking how users heterogeneously express depressive risk after screening. A monolithic...Online social media posts provide scalable signals for early depression screening, and recent studies mainly improve pre-classification evidence through risk-post selection, symptom grounding, and clinically informed feature construction. However, these screening-stage designs often leave final decisions to a single detector, overlooking how users heterogeneously express depressive risk after screening. A monolithic...

Beyond travel mode: urban context shapes active mobility's mental health effects over timeBeyond travel mode: urban context shapes active mobility's mental health effects over time

Shujuan Chen, Yue Li, Ying Jin

Active mobility is widely promoted for sustainable and healthier living, but whether it translates into equitable mental health benefits across individuals and places over time remains unknown. Using causal machine learning and causal deep learning in 264168 UK adults, we find substantial inequalities in individualized effects of active mobility on anxiety, depression, and common mental disorders. These inequalities widen...Active mobility is widely promoted for sustainable and healthier living, but whether it translates into equitable mental health benefits across individuals and places over time remains unknown. Using causal machine learning and causal deep learning in 264168 UK adults, we find substantial inequalities in individualized effects of active mobility on anxiety, depression, and common mental disorders. These inequalities widen...

Explainable AI for Screening Abuse-Related Trauma in Bangladeshi Children: A Training-Free Multimodal Framework Evaluated on Noise-Aware Synthetic DataExplainable AI for Screening Abuse-Related Trauma in Bangladeshi Children: A Training-Free Multimodal Framework Evaluated on Noise-Aware Synthetic Data

Salma Hoque Talukdar Koli, Fahima Haque Talukder Jely

Bangladesh has an estimated 1.17 mental-health professionals per 100,000 population and only six child psychiatrists nationwide. No Bengali-language, culturally adapted tool exists for early screening of abuse-related psychological trauma in children. We present ShishuRaksha AI, a decision-support (not diagnostic) framework that fuses four screening modalities: validated questionnaires (SDQ, CPSS), Bengali narrative text,...Bangladesh has an estimated 1.17 mental-health professionals per 100,000 population and only six child psychiatrists nationwide. No Bengali-language, culturally adapted tool exists for early screening of abuse-related psychological trauma in children. We present ShishuRaksha AI, a decision-support (not diagnostic) framework that fuses four screening modalities: validated questionnaires (SDQ, CPSS), Bengali narrative text,...

Can Conversational Temporal Dynamics Improve Depression Detection in Dyads? A Preliminary Investigation in Multi-Modality PerspectivesCan Conversational Temporal Dynamics Improve Depression Detection in Dyads? A Preliminary Investigation in Multi-Modality Perspectives

Hanie Kang, Huang-Cheng Chou, Sudarsana Reddy Kadiri, Shrikanth Narayanan

Automatic depression detection from clinical interviews typically models the semantic content and acoustic characteristics of participant speech. However, the interactional timing between the clinician and participant remains comparatively under-modeled. We investigate conversational temporal dynamics, specifically dyadic turn-pair timing, as a primary modality fused with self-supervised encoders. Evaluated on the DAIC-WOZ...Automatic depression detection from clinical interviews typically models the semantic content and acoustic characteristics of participant speech. However, the interactional timing between the clinician and participant remains comparatively under-modeled. We investigate conversational temporal dynamics, specifically dyadic turn-pair timing, as a primary modality fused with self-supervised encoders. Evaluated on the DAIC-WOZ...

psytechlab at CLPsych 2026: Utilising Natural Language Processing methods and Large Language Models for Social Media Text Analysispsytechlab at CLPsych 2026: Utilising Natural Language Processing methods and Large Language Models for Social Media Text Analysis

Igor Buyanov, Nafisa Valieva, Ekaterina Mazurina

Social media posts are a rich and valuable source of data for analyzing mental health states and users' well-being using automated analysis tools. In this work, we demonstrate how we used a range of Natural Language Processing (NLP) methods, including Long Short-Term Memory (LSTM), BERT-based models, and Large Language Models (LLMs), for self-state and well-being analysis and summarization during the CLPsych Shared Task 2026....Social media posts are a rich and valuable source of data for analyzing mental health states and users' well-being using automated analysis tools. In this work, we demonstrate how we used a range of Natural Language Processing (NLP) methods, including Long Short-Term Memory (LSTM), BERT-based models, and Large Language Models (LLMs), for self-state and well-being analysis and summarization during the CLPsych Shared Task 2026....

Where do LLMs Fall Short in CBT-Guided Affective Reasoning?Where do LLMs Fall Short in CBT-Guided Affective Reasoning?

Vaishnavi Sinha, Pooja Guttal, Pranay Deep Reddy Katike, Vishal Sinha, Gerald Ndawula, Lira Yoon

Cognitive Behavioral Therapy (CBT) provides a structured framework for understanding a user's mental state by examining the interaction between cognitive and behavioral factors. However, out-of-the-box LLMs respond fluently and empathetically, yet collapse into validation & reflection, regardless of what the user actually needs. They know theoretical CBT (scoring up to 96% accuracy on licensing exam questions) but fail to...Cognitive Behavioral Therapy (CBT) provides a structured framework for understanding a user's mental state by examining the interaction between cognitive and behavioral factors. However, out-of-the-box LLMs respond fluently and empathetically, yet collapse into validation & reflection, regardless of what the user actually needs. They know theoretical CBT (scoring up to 96% accuracy on licensing exam questions) but fail to...

Speaker-Aware Temporal Aggregation Strategies on Segment Representations for Depression Detection in Dyadic Interaction: A Benchmark StudySpeaker-Aware Temporal Aggregation Strategies on Segment Representations for Depression Detection in Dyadic Interaction: A Benchmark Study

Anisha Pattanayak, Huang-Cheng Chou, Shrikanth Narayanan, Sudarsana Reddy Kadiri

Speech-based depression detection compresses features from short audio segments into one speaker-level decision, a step called temporal aggregation rarely studied on its own. Most benchmarks fix a single self-supervised encoder and a single hand-picked layer, so a reported gain may reflect the pipeline rather than the aggregation method itself. We introduce DEPOOL, a controlled benchmark that compares six aggregation...Speech-based depression detection compresses features from short audio segments into one speaker-level decision, a step called temporal aggregation rarely studied on its own. Most benchmarks fix a single self-supervised encoder and a single hand-picked layer, so a reported gain may reflect the pipeline rather than the aggregation method itself. We introduce DEPOOL, a controlled benchmark that compares six aggregation...

Mental Health Disorder Detection Beyond Social Media: A Systematic Review of Available DatasetsMental Health Disorder Detection Beyond Social Media: A Systematic Review of Available Datasets

Sadiya Sayara Chowdhury Puspo, Ana-Maria Bucur, Stevie Chancellor, Özlem Uzuner, Marcos Zampieri

Detecting mental health disorders in a timely manner is an important societal challenge. NLP and machine learning (ML) methods used to assist with detection rely on data collected primarily from social media. However, such datasets often have sampling biases and inherent ethical and privacy issues. One avenue to overcome these limitations is non-social media data. We present the first comprehensive review of non-social media,...Detecting mental health disorders in a timely manner is an important societal challenge. NLP and machine learning (ML) methods used to assist with detection rely on data collected primarily from social media. However, such datasets often have sampling biases and inherent ethical and privacy issues. One avenue to overcome these limitations is non-social media data. We present the first comprehensive review of non-social media,...

See the Emotion: A Facial Emoji Proxy Modeling for EEG Emotion RecognitionSee the Emotion: A Facial Emoji Proxy Modeling for EEG Emotion Recognition

Jingjing Hu, Guo Dan, Haofan Cheng, Ying Zeng, Zhan Si, Jinxing Zhou

Despite the high accuracy of EEG-based emotion recognition, existing models remain opaque "black boxes", lacking semantic grounding between abstract neural features and human-interpretable states. In this paper, we reframe EEG explainability as a cross-modal generation task, shifting the paradigm from feature attribution to behavioral visualization. We introduce Facial Emoji Proxy Modeling, a novel framework that translates...Despite the high accuracy of EEG-based emotion recognition, existing models remain opaque "black boxes", lacking semantic grounding between abstract neural features and human-interpretable states. In this paper, we reframe EEG explainability as a cross-modal generation task, shifting the paradigm from feature attribution to behavioral visualization. We introduce Facial Emoji Proxy Modeling, a novel framework that translates...

Layer-wise Cross-Lingual Depression Detection from Speech: Analysis with Contrastive AlignmentLayer-wise Cross-Lingual Depression Detection from Speech: Analysis with Contrastive Alignment

Anisha Pattanayak, Hanie Kang, Huang-Cheng Chou, Shrikanth Narayanan, Sudarsana Reddy Kadiri

Significant disparities exist in the diagnosis and clinical presentation of depression across different linguistic populations. Speech-based depression detection performs well monolingually, but cross-lingual generalization remains an open challenge. A key reason is that prior work uses segment-level random splits without speaker grouping, leading to identity leakage that inflates reported metrics. We propose CLeaD, a...Significant disparities exist in the diagnosis and clinical presentation of depression across different linguistic populations. Speech-based depression detection performs well monolingually, but cross-lingual generalization remains an open challenge. A key reason is that prior work uses segment-level random splits without speaker grouping, leading to identity leakage that inflates reported metrics. We propose CLeaD, a...

Latest Papers - July 03, 2026Latest Papers - July 03, 2026

github-actions[bot], LbsTempest/Daily-ArXiv-Subscription

**Please check the [Github page](https://github.com/LbsTempest/Daily-ArXiv-Subscription) for a better reading experience and more papers.** ## Speech Synthesis | **Title** | **Link** | **Date** | **Comment** | | --- | --- | --- | --- | | **[A Geometric Perspective on Composable Emotion Steering in Last30Days signal for embodied emotional intelligence robot emotion, surfaced from GitHub public activity in the latest 30-day window.**Please check the [Github page](https://github.com/LbsTempest/Daily-ArXiv-Subscription) for a better reading experience and more papers.** ## Speech Synthesis | **Title** | **Link** | **Date** | **Comment** | | --- | --- | --- | --- | | **[A Geometric Perspective on Composable Emotion Steering in Last30Days signal for embodied emotional intelligence robot emotion, surfaced from GitHub public activity in the latest 30-day window.

feat: add JuliaFormatter style enforcementfeat: add JuliaFormatter style enforcement

rmems, rmems/XAIDissect_Viz.jl

CodeAnt AI is reviewing your PR. --- ### Thanks for using CodeAnt! 🎉 We're free for open-source projects. if you're enjoying it, help us grow by sharing. [Share on X](https://twitter.com/intent/tweet?text=Just%20tried%20%40CodeAntAI%20for%20automated%20code%20review%20and%20I%27m%20impressed%21%20Free%20for%20open%20source%20wit... <!-- This is an... Last30Days signal for AI mental health digital wellbeing, surfaced from GitHub public activity in the latest 30-day window.CodeAnt AI is reviewing your PR. --- ### Thanks for using CodeAnt! 🎉 We're free for open-source projects. if you're enjoying it, help us grow by sharing. [Share on X](https://twitter.com/intent/tweet?text=Just%20tried%20%40CodeAntAI%20for%20automated%20code%20review%20and%20I%27m%20impressed%21%20Free%20for%20open%20source%20wit... <!-- This is an... Last30Days signal for AI mental health digital wellbeing, surfaced from GitHub public activity in the latest 30-day window.

Copewell: A Multi-Agent Swarm Architecture for Equitable Mental Wellness SupportCopewell: A Multi-Agent Swarm Architecture for Equitable Mental Wellness Support

Seren Yenikent, Jack Vinijtrongjit, Katherine Ng

Mental health disorders affect nearly one billion people globally, yet 75% of individuals in low- and middle-income countries receive no treatment due to workforce shortages, cost barriers, and stigma. Current AI-powered wellness solutions predominantly rely on single-mode conversational interfaces that suffer high abandonment rates and fail to provide measurable, immediate relief calibrated to users' dynamic emotional...Mental health disorders affect nearly one billion people globally, yet 75% of individuals in low- and middle-income countries receive no treatment due to workforce shortages, cost barriers, and stigma. Current AI-powered wellness solutions predominantly rely on single-mode conversational interfaces that suffer high abandonment rates and fail to provide measurable, immediate relief calibrated to users' dynamic emotional...

Pattern-Calibrated Multimodal Prediction under Blockwise MissingnessPattern-Calibrated Multimodal Prediction under Blockwise Missingness

Junhan Yu, Kejian Zhang, Doudou Zhou, Guojun Zhu

Blockwise missingness in multimodal data is usually treated as an incomplete-input problem. We instead focus on prediction for a prespecified observed-modality pattern, where the observed modality set determines the information on which the prediction rule can condition. A procedure that imputes missing modalities, zero-fills unobserved modalities, or trains a single pooled predictor may borrow information across patterns,...Blockwise missingness in multimodal data is usually treated as an incomplete-input problem. We instead focus on prediction for a prespecified observed-modality pattern, where the observed modality set determines the information on which the prediction rule can condition. A procedure that imputes missing modalities, zero-fills unobserved modalities, or trains a single pooled predictor may borrow information across patterns,...

EmoteGPT: 3D Human Facial Expressions from Natural Language DescriptionsEmoteGPT: 3D Human Facial Expressions from Natural Language Descriptions

Haoran Wang, Mohit Mendiratta, Christian Theobalt, Adam Kortylewski

Precise control of 3D facial expressions from text is crucial for virtual avatars, animation, and human-computer interaction, yet existing text-to-3D methods jointly generate identity, expression, and texture, making fine-grained expression control difficult. We instead formulate text-driven expression synthesis as a regression problem in the disentangled parameter space of a 3D Morphable Model (3DMM). This setting, however,...Precise control of 3D facial expressions from text is crucial for virtual avatars, animation, and human-computer interaction, yet existing text-to-3D methods jointly generate identity, expression, and texture, making fine-grained expression control difficult. We instead formulate text-driven expression synthesis as a regression problem in the disentangled parameter space of a 3D Morphable Model (3DMM). This setting, however,...

The Individual-Targeting Assumption: A Systematic Review of Proactive Robots in Human Group SettingsThe Individual-Targeting Assumption: A Systematic Review of Proactive Robots in Human Group Settings

Tauhid Tanjim, Tasmia Mayen, Malte F. Jung, Susan R. Fussell

Proactive robots are increasingly deployed in public environments where people are encountered not as isolated individuals but as members of cohesive social groups. Yet whether the prevailing design paradigm in proactive human-robot interaction (HRI) accounts for the relational structure that defines a group as a social unit remains largely unexamined. Through a systematic review of 63 proactive HRI studies in group settings...Proactive robots are increasingly deployed in public environments where people are encountered not as isolated individuals but as members of cohesive social groups. Yet whether the prevailing design paradigm in proactive human-robot interaction (HRI) accounts for the relational structure that defines a group as a social unit remains largely unexamined. Through a systematic review of 63 proactive HRI studies in group settings...

2026 BAIR Graduate Showcase2026 BAIR Graduate Showcase

BAIR Blog

Congratulations to the Berkeley Artificial Intelligence Research (BAIR) Lab class of 2026! This year, BAIR celebrates another remarkable group of Ph.D. graduates whose curiosity, creativity, and perseverance have pushed the frontiers of artificial intelligence and machine learning. Their work spans the breadth of modern AI — robotics and embodied...Congratulations to the Berkeley Artificial Intelligence Research (BAIR) Lab class of 2026! This year, BAIR celebrates another remarkable group of Ph.D. graduates whose curiosity, creativity, and perseverance have pushed the frontiers of artificial intelligence and machine learning. Their work spans the breadth of modern AI — robotics and embodied...

Quantifying the Affective Gap: A Zero-Shot Evaluation of LLMs on Fine-Grained Emotion TaxonomiesQuantifying the Affective Gap: A Zero-Shot Evaluation of LLMs on Fine-Grained Emotion Taxonomies

Lawrence Obiuwevwi, Krzysztof J. Rechowicz, Jessica M. Johnson, Vikas Ashok, Sachin Shetty, Sampath Jayarathna

Emotion recognition in natural language is a foundational challenge in affective computing, with critical implications for human-computer interaction, mental health support, and conversational AI. This paper presents a rigorous, unified zero-shot evaluation of three leading commercial large language models: Claude (claude-sonnet-4-6), ChatGPT (GPT-5.4), and Gemini (gemini-2.5-flash). The models were queried through their...Emotion recognition in natural language is a foundational challenge in affective computing, with critical implications for human-computer interaction, mental health support, and conversational AI. This paper presents a rigorous, unified zero-shot evaluation of three leading commercial large language models: Claude (claude-sonnet-4-6), ChatGPT (GPT-5.4), and Gemini (gemini-2.5-flash). The models were queried through their...

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion RecognitionPRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition

Xin Zhou, Xiang Zhang, Hao Deng, Lijun Yin

Electroencephalogram (EEG) captures endogenous brain activity with high temporal fidelity and holds substantial promise for precise emotion decoding. However, channel redundancy and pronounced inter-subject variability remain key obstacles to scalable generalization. To address these limitations, we propose a novel framework termed PRioritized channel Importance with Semi-supervised doMain adaptation (PRISM), enabling...Electroencephalogram (EEG) captures endogenous brain activity with high temporal fidelity and holds substantial promise for precise emotion decoding. However, channel redundancy and pronounced inter-subject variability remain key obstacles to scalable generalization. To address these limitations, we propose a novel framework termed PRioritized channel Importance with Semi-supervised doMain adaptation (PRISM), enabling...

Gemma 4 on Cerebras - The Fastest Inference Is Now MultimodalGemma 4 on Cerebras - The Fastest Inference Is Now Multimodal

Tiberium, Hacker News

Gemma 4 on Cerebras - The Fastest Inference Is Now Multimodal Last30Days signal for multimodal affective computing speech emotion, surfaced from Hacker News public activity in the latest 30-day window.Gemma 4 on Cerebras - The Fastest Inference Is Now Multimodal Last30Days signal for multimodal affective computing speech emotion, surfaced from Hacker News public activity in the latest 30-day window.

Introducing TabFM: A zero-shot foundation model for tabular dataIntroducing TabFM: A zero-shot foundation model for tabular data

Google Research

Selected from Google Research's public feed for its relevance to AI Research and applied AI systems.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。

SkillOpt: Agent skills as trainable parametersSkillOpt: Agent skills as trainable parameters

Microsoft Research

AI agents often fail because their instructions, or skills, are manually modified with no guarantee of improvement. Learn how SkillOpt turns skill editing into a training process, making agent behavior more reliable without changing model weights. The post SkillOpt: Agent skills as trainable parameters appeared first on Microsoft Research .AI agents often fail because their instructions, or skills, are manually modified with no guarantee of improvement. Learn how SkillOpt turns skill editing into a training process, making agent behavior more reliable without changing model weights. The post SkillOpt: Agent skills as trainable parameters appeared first on Microsoft Research .

A Fair and Transparent Framework for Speech-Based Depression Detection: Balancing Interpretability and PerformanceA Fair and Transparent Framework for Speech-Based Depression Detection: Balancing Interpretability and Performance

Mariel Estevez, Alfonso Ortega, Antonio Miguel, Eduardo Lleida

While speech provides rich, non-invasive biomarkers for mental-health assessment, clinical adoption is limited by opaque models and potential demographic bias. In this work we propose a methodological framework to evaluate robustness and interpretability for automated depression detection on the extended DAIC-WOZ dataset using low-complexity machine learning baselines (RF, SVM, and MLP) chosen to mitigate overfitting and...While speech provides rich, non-invasive biomarkers for mental-health assessment, clinical adoption is limited by opaque models and potential demographic bias. In this work we propose a methodological framework to evaluate robustness and interpretability for automated depression detection on the extended DAIC-WOZ dataset using low-complexity machine learning baselines (RF, SVM, and MLP) chosen to mitigate overfitting and...

MAC-Lab Official Website Released实验室主页发布：sxhfut.github.io

The new bilingual MAC-Lab website presents research directions, industry solutions, academic impact, lab news, frontier sharing, media coverage, student training, and collaboration channels.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。

CausalSymptom Accepted by IEEE Transactions on Affective Computing与中国科学技术大学联合研究成果被 TAC 录用

CausalSymptom studies causal disentangled representation learning for depression severity estimation from transcribed clinical interviews, connecting clinical dialogue, interpretability, and psychological 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。

Modeling Latent Background Information in Multiturn Dialogues Using Diffusion Model Published in IEEE Transactions on Artificial Intelligence扩散增强多轮对话潜在背景建模研究发表于 IEEE Transactions on Artificial Intelligence

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.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。

ERMoV: Modeling Affective Mental States via Emotion Regulation for Dialogue Emotion Recognition Published in IEEE Transactions on Affective ComputingERMoV 情绪调节驱动对话情绪识别研究发表于 IEEE Transactions on Affective Computing

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.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。

Decoding Emotion, Empowering Mind-Body Health解码情感，智惠身心

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.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。

Causal-ESC Accepted by IEEE/ACM Transactions on Audio, Speech, and Language ProcessingCausal-ESC 情感支持对话因果检测研究发表于 IEEE/ACM TASLP

Causal-ESC captures cause-and-effect dynamics in emotional support conversation, connecting affective NLP, empathetic dialogue, and psychologically meaningful interaction modeling.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。

Adaptive Sample Mining for Facial Expression Recognition Published in IEEE Transactions on Fuzzy Systems面部表情识别自适应样本挖掘研究发表于 IEEE Transactions on Fuzzy Systems

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.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。

MultiAgentESC Accepted by EMNLP 2025MultiAgentESC 情感支持对话多智能体框架发表于 EMNLP 2025

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.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。

Multimodal Affective Computing and Intervention Technology Wins Silver Award普适场景多模态情感计算与干预技术获国际发明展银奖

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.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。

UniEmoX Published in IEEE Transactions on Image ProcessingUniEmoX 发表在 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.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。

Lab Contributes to a Group Standard for Healthy Residential Environments实验室参编健康住区环境保障智能系统设计技术导则

The lab's human-factor affective computing technology entered standardization work for intelligent systems supporting 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。

Social-Psychological Dual-Dimensional Clustering Modeling Published at IPMLP 2025社会-心理双维聚类建模研究发表于 IPMLP 2025

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.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。

Empathy Level Alignment via Reinforcement Learning Published in IEEE Transactions on Affective Computing共情水平对齐强化学习研究发表于 IEEE Transactions on Affective Computing

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.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。

PsycoLLM Published in IEEE Transactions on Computational Social SystemsPsycoLLM 心理理解与评估研究发表于 IEEE TCSS

PsycoLLM enhances large language models for psychological understanding and evaluation, linking affective NLP, psychological assessment, and the lab's broader psychological computing platform direction.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。

Temporal-Frequency State Space Duality Published at ICASSP 2025语音情绪识别时频状态空间对偶方法发表于 ICASSP 2025

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.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。

DEFormer Published at ICASSP 2025DEFormer 低光图像与暗视觉增强研究发表于 ICASSP 2025

DEFormer studies DCT-driven enhancement transformers for low-light image and dark vision, expanding the lab's multimodal AI and deployable perception toolbox.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。