A VLM-based emotion recognition system for human-robot collaboration achieves higher semantic and sentiment alignment with human annotations than a CNN baseline and results in preferred adaptive robot behavior in a user study.
Vllms provide better context for emotion understanding through common sense reasoning
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2representative citing papers
PCMECL improves speech-preserving facial expression manipulation by learning personalized prompts from individual visuals and using feature differencing to align visual and semantic changes from VLMs.
citing papers explorer
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"I'm Not Mad, Just Focused'': Understanding Human Emotions in Human-Robot Collaboration
A VLM-based emotion recognition system for human-robot collaboration achieves higher semantic and sentiment alignment with human annotations than a CNN baseline and results in preferred adaptive robot behavior in a user study.
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Personalized Cross-Modal Emotional Correlation Learning for Speech-Preserving Facial Expression Manipulation
PCMECL improves speech-preserving facial expression manipulation by learning personalized prompts from individual visuals and using feature differencing to align visual and semantic changes from VLMs.