From Relevance to Utility: Evidence Retrieval with Feedback for Fact Verification
Hengran Zhang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Yixing Fan, Xueqi Cheng · 2023
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.1