Emotion Across Speech and Faces: Shared Affective Mechanisms in Multimodal Foundation Models
Researchers discover cross-modal 'emotion-sensitive neurons' that allow AI to process human affect through a shared internal language.
Modern multimodal foundation models (MFMs) have made rapid progress on tasks requiring integrated perception across speech, vision, and language, including emotion recognition. However, it remains unclear whether they recognize speech and facial emotion through shared affective f...
ArXiv CS.CL
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This research reveals that multimodal models process emotions through shared internal mechanisms rather than isolated sensory silos. By mapping these specific emotional neurons, researchers can now precisely intervene in how AI interprets human expressions across both voice and vision.
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