Optimizing Multimodal Emotion Analysis Through Agentic Prompt Patching
This research introduces a verification-based framework that refines multimodal emotion reasoning in AI agents. Instead of retraining models, the system identifies specific component failures and applies targeted prompt updates to improve performance.