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From Topical Relevance to Answerability: Entailment Distillation for Conversational Retrieval
Existing conversational retrievers commonly treat topical relevance as a proxy for answerability. However, a passage that closely matches the dialogue context is not necessarily the one that supports the correct answer. We identify this mismatch as a systematic answerability gap. To address this iss
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