#emotion-recognition

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4.9 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.6 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.4 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.7 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.3 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.3 CoMem Paper Proposes Shared and Individual Memory Design for LLM Multi-Agent Systems — 1 src1.3 Paper proposes evolving context parameterization for large language models — 1 src1.3 Fine-Tuning Vision-Language Models with Listener Gaze for Referring Expressions — 1 src4.9 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.6 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.4 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.7 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.3 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.3 CoMem Paper Proposes Shared and Individual Memory Design for LLM Multi-Agent Systems — 1 src1.3 Paper proposes evolving context parameterization for large language models — 1 src1.3 Fine-Tuning Vision-Language Models with Listener Gaze for Referring Expressions — 1 src

2 curated events

papersTODAY 04:00 UTC

ReH-FUSE: Reliability-Aware Fusion of Experts for Multimodal Emotion Recognition

A new arXiv paper introduces ReH-FUSE, a method for multimodal emotion recognition in conversation that accounts for how much each evidence source can be trusted in a given instance. The approach hierarchically combines expert predictions so that lexical, vocal, and other cues are weighted according to their reliability rather than treated as equally informative. It targets the problem that different modalities may dominate depending on the conversational context.

multimodal/emotion-recognition/fusion/arxiv

papersSEP 10 04:00 UTC

Researchers propose relational paradigm for affective computing in vocal interactions

A new arXiv paper argues that affective computing's dominant approach, which assigns discrete emotion labels or arousal/valence scores to individual speakers, is inadequate for understanding emotional life as it happens between people. The authors instead build on the ideas of affective resonance and vitality affects to model vocal exchanges as dynamic, shared interaction fields. The work reframes emotion recognition as a relational process rather than the classification of isolated internal states.

affective-computing/emotion-recognition/vocal-interaction/theory