BiDeV: Bilateral Defusing Verification for Complex Claim Fact-Checking
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Abstract (arXiv)
Complex claim fact-checking performs a crucial role in disinformation detection. However, existing fact-checking methods struggle with claim vagueness, specifically in effectively handling latent information and complex relations within claims. Moreover, evidence redundancy, where nonessential information complicates the verification process, remains a significant issue. To tackle these limitations, we propose Bilateral Defusing Verification (BiDeV), a novel fact-checking working-flow framework integrating multiple role-played LLMs to mimic the human-expert fact-checking process. BiDeV consists of two main modules: Vagueness Defusing identifies latent information and resolves complex relations to simplify the claim, and Redundancy Defusing eliminates redundant content to enhance the evidence quality. Extensive experimental results on two widely used challenging fact-checking benchmarks (Hover and Feverous-s) demonstrate that our BiDeV can achieve the best performance under both gold and open settings. This highlights the effectiveness of BiDeV in handling complex claims and ensuring precise fact-checking
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 20 of its 36 references that are in the map. First posted on arXiv 22 Feb 2025.
Builds on
20 of 36 references.
References · 20
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8 more
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Citing papers per year: 2025: 6; 2026: 2.
8 papers.
- 2025The Truth Becomes Clearer Through Debate! Multi-Agent Systems with Large Language Models Unmask Fake Newscited by 29
- 2025MobileSteward: Integrating Multiple App-Oriented Agents with Self-Evolution to Automate Cross-App Instructionscited by 16
- 2025Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Modelscited by 13
- 2025Veri-R1: Toward Precise and Faithful Claim Verification via Online Reinforcement Learningcited by 5
- 2025T^2Agent A Tool-augmented Multimodal Misinformation Detection Agent with Monte Carlo Tree Searchcited by 4
- 2025Coordinating Search-Informed Reasoning and Reasoning-Guided Search in Claim Verificationcited by 4
- 2026Retrieve-Refine-Calibrate: A Framework for Complex Claim Fact-Checkingcited by 0
- 2026The Alignment Bottleneck in Decomposition-Based Claim Verificationcited by 0
- 2026The Alignment Bottleneck in Decomposition-Based Claim Verification11 Feb 2026
- 2026Retrieve-Refine-Calibrate: A Framework for Complex Claim Fact-Checking23 Jan 2026
- 2025Veri-R1: Toward Precise and Faithful Claim Verification via Online Reinforcement Learning2 Oct 2025
- 2025Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Models5 Aug 2025
- 2025Coordinating Search-Informed Reasoning and Reasoning-Guided Search in Claim Verification9 Jun 2025
- 2025T^2Agent A Tool-augmented Multimodal Misinformation Detection Agent with Monte Carlo Tree Search26 May 2025
- 2025The Truth Becomes Clearer Through Debate! Multi-Agent Systems with Large Language Models Unmask Fake News13 May 2025
- 2025MobileSteward: Integrating Multiple App-Oriented Agents with Self-Evolution to Automate Cross-App Instructions24 Feb 2025