SPIN Unprocessed October 26, 2026 ai_technology research
An Agentic Approach with Evidence-Grounded Verification for Multimodal Emotion Reasoning in Conversation
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arXiv:2610.31685v1 Announce Type: new Abstract: LLM-based multimodal emotion reasoning systems perform well on standard benchmarks, but improving them through instruction tuning can be computationally expensive. Agentic pipelines built from frozen models avoid this cost, but introduce a different challenge: when a prediction is wrong, the system must identify which agent or stage caused the error. We address this problem with an agentic framework for traceable multimodal emotion reasoning and pr
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