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Deceptive Grounding: Entity Attribution Failure in Clinical RAG

A new paper identifies 'deceptive grounding' (DG), a failure mode in clinical retrieval-augmented generation where a model's response is fully grounded in retrieved documents but attributes evidence to the wrong entity (e.g., drug Y's evidence presented as drug X's). DG passes all standard faithfulness, hallucination, and citation checks, making it invisible to current evaluation methods.

0 engagement·1 source·Fri, Jul 10, 2026, 12:29 PM
The paper, titled 'Deceptive Grounding: Entity Attribution Failure in Clinical Retrieval-Augmented Generation' and posted on arXiv on 2026-07-10, demonstrates that existing RAG evaluation metrics—faithfulness, hallucination detection, and citation accuracy—do not verify whether retrieved evidence is attributed to the correct entity. In a clinical setting, a RAG system can produce a response that is factually accurate per the retrieved documents but misattributes evidence from one drug to another. The authors term this 'deceptive grounding' and argue that new evaluation methods are needed to detect entity-level attribution errors.

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Deceptive Grounding(concept)Retrieval-Augmented Generation(concept)Clinical RAG(tool)

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