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Relevance Is Not Sufficient Evidence: Detecting Evidence Gaps Before Generation in RAG

Chen, Suting et al.
arXiv (All) · Papers
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computation-and-languageinformation-retrievalmachine-learning
Retrieval-augmented generation (RAG) grounds large language models in external sources, but retrieved passages often name the right entities without providing the facts needed to answer. Even when instructed to abstain, 12 generators answer 40.0-99.3% of insufficient-evidence questions. Training gen
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