A framework converts interpretable facial and acoustic features into language descriptions, feeds them to a pretrained LM for semantic embeddings, and uses those embeddings as priors to improve valence and arousal change prediction on Aff-Wild2 and SEWA while remaining transparent.
Aff-wild2: Ex- tending the aff-wild database for affect recognition
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Facial expression signals via prompt integration improve empathetic responsiveness in LLM-based tutoring systems.
citing papers explorer
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LaScA: Language-Conditioned Scalable Modelling of Affective Dynamics
A framework converts interpretable facial and acoustic features into language descriptions, feeds them to a pretrained LM for semantic embeddings, and uses those embeddings as priors to improve valence and arousal change prediction on Aff-Wild2 and SEWA while remaining transparent.
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Facial-Expression-Aware Prompting for Empathetic LLM Tutoring
Facial expression signals via prompt integration improve empathetic responsiveness in LLM-based tutoring systems.