CORRECT: Context- and Reference-Augmented Reasoning and Prompting for Fact-Checking

• URL: http://arxiv.org/abs/2502.09635v1
• Date: Sun, 09 Feb 2025 01:41:15 GMT
• Title: CORRECT: Context- and Reference-Augmented Reasoning and Prompting for Fact-Checking
• Authors: Delvin Ce Zhang, Dongwon Lee,
• Abstract summary: We propose a novel method, Context- and Reference-augmented Reasoning and Prompting.<n>For evidence reasoning, we construct a three-layer evidence graph with evidence, context, and reference layers.<n>For verdict prediction, we design evidence-conditioned prompt encoder, which produces unique prompt embeddings for each claim.
• Score: 14.890042094350411
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Fact-checking the truthfulness of claims usually requires reasoning over multiple evidence sentences. Oftentimes, evidence sentences may not be always self-contained, and may require additional contexts and references from elsewhere to understand coreferential expressions, acronyms, and the scope of a reported finding. For example, evidence sentences from an academic paper may need contextual sentences in the paper and descriptions in its cited papers to determine the scope of a research discovery. However, most fact-checking models mainly focus on the reasoning within evidence sentences, and ignore the auxiliary contexts and references. To address this problem, we propose a novel method, Context- and Reference-augmented Reasoning and Prompting. For evidence reasoning, we construct a three-layer evidence graph with evidence, context, and reference layers. We design intra- and cross-layer reasoning to integrate three graph layers into a unified evidence embedding. For verdict prediction, we design evidence-conditioned prompt encoder, which produces unique prompt embeddings for each claim. These evidence-conditioned prompt embeddings and claims are unified for fact-checking. Experiments verify the strength of our model.

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