AI RESEARCH
Feedback Adaptation for Retrieval-Augmented Generation
arXiv CS.CL
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ArXi:2604.06647v1 Announce Type: new Retrieval-Augmented Generation (RAG) systems are typically evaluated under static assumptions, despite being frequently corrected through user or expert feedback in deployment. Existing evaluation protocols focus on overall accuracy and fail to capture how systems adapt after feedback is