Relevant Is Not Warranted: Evidence-Force Calibration for Cited RAG 文章

ArXiv CS.AI2026-05-28NEWSen作者: Pin Qian, Su Wang, Xiaoyuan Wang, Yihang Chen, Wenxuan Xu, Qiaolin Yu, Shuhuai Lin, Sipeng Zhang, Junxian You, Xinpeng Wei

摘要

arXiv:2605.28044v1 Announce Type: new Abstract: Cited RAG evaluation often treats visible sources as a grounding signal, but a real, topically relevant citation can still under-warrant the attached wording. We study this diagnostic failure as citation laundering: a related source is presented as warrant for an over-strong claim. We introduce FORCEBENCH, a contrastive stress test for evidence-force calibration. Each item holds a cited passage fixed and pairs an evidence-calibrated claim with a localized force-raised variant across five operational axes: relation, modality, scope, temporal validity, and numeric specificity. A calibrated evaluator should score the evidence-calibrated claim higher. Headline experiments use a fixed, locality-filtered 198-pair evaluation set. A citation-presence sanity check is uninformative by design; token and entity overlap still violate monotonicity on 32.8--36.4% of pairs.

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