Retrieval-enhanced methods have become a primary approach in fact verification (FV); it requires reasoning over multiple retrieved pieces of evidence to verify the integrity of a claim. To retrieve evidence, existing work often employs off-the-shelf retrieval models whose design is based on the probability ranking principle. We argue that, rather than relevance, for FV we need to focus on the utility that a claim verifier derives from the retrieved evidence. We introduce the feedback-based evidence retriever(FER) that optimizes the evidence retrieval process by incorporating feedback from the claim verifier. As a feedback signal we use the divergence in utility between how effectively the verifier utilizes the retrieved evidence and the ground-truth evidence to produce the final claim label. Empirical studies demonstrate the superiority of FER over prevailing baselines.

翻译：检索增强方法已成为事实验证的主要途径，该方法需对多条检索证据进行推理以验证声明的真实性。现有研究常采用基于概率排序原则的现成检索模型来获取证据。本文指出，事实验证应关注声明验证者从检索证据中获取的效用，而非单纯的相关性。我们提出基于反馈的证据检索器（FER），通过整合声明验证者的反馈信号来优化证据检索过程。该反馈信号衡量的是验证者利用检索证据与真实证据得出最终声明标签时，两者效用差异的离散程度。实验研究表明，FER在性能上显著优于主流基准方法。