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cs.CL2026
Deceptive Grounding: Entity Attribution Failure in Clinical Retrieval-Augmented Generation
Cedric Caruzzo, Donggeun Yoo, Tae Soo Kim
Retrieval-augmented generation evaluation checks whether model claims are factually grounded in retrieved documents. It does not check whether retrieved evidence is attributed to t…
cs.CL2025
CUPID: Evaluating Personalized and Contextualized Alignment of LLMs from Interactions
Tae Soo Kim, Yoonjoo Lee, Yoonah Park +3
Personalization of Large Language Models (LLMs) often assumes users hold static preferences that reflect globally in all tasks. In reality, humans hold dynamic preferences that cha…