EmoLLM: Appraisal-Grounded Cognitive-Emotional Co-Reasoning in Large Language Models
Large language models (LLMs) demonstrate strong cognitive intelligence (IQ), yet many real-world interactions also require emotional intelligence (EQ) to produce responses that are both factually reliable and emotionally appropriate. In settings such as emotional support, technical assistance, and consultation, effective dialogue depends on how situations are appraised with respect to the user's needs, goals, and coping capacity. Inspired by appraisal theory, we propose EmoLLM, an appraisal-grounded framework for IQ/EQ co-reasoning in dialogue. EmoLLM uses an explicit Appraisal Reasoning Graph (ARG) to structure intermediate reasoning over contextual facts, inferred user needs, appraisal ...
| Authors | Yifei Zhang, Mingyang Li, Henry Gao et al. |
|---|---|
| Primary category | cs.CL |
| Published | 17 March 2026 |
| Last updated at source | 17 March 2026 |
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