数字图书馆论坛2026，Vol.22Issue(5)：20-33,14.DOI:10.3772/j.issn.1673-2286.2026.05.003
证据链增强的多智能体分组讨论事实核查框架研究
Research on an Evidence Chain Enhanced Multi-Agent Group Discussion Fact-Checking Framework
摘要
Abstract
Fact-checking serves as a critical approach for identifying and mitigating misinformation.However,individual large language models(LLMs)suffer from inherent limitations in fact-checking tasks,including hallucination issues,insufficient interpretability,and limited accuracy.This study proposes an Evidence Chain Enhanced Multi-Agent Group Discussion Fact-Checking Framework to improve the accuracy,robustness,and explainability of fact-checking systems.The proposed framework consists of a moderator agent responsible for task orchestration,result aggregation,and consensus adjudication,along with three specialized fact-checking agent groups focusing on scientific evidence,media evidence,and factual evidence,respectively.Within each group,agents follow a standardized fact-checking workflow involving evidence retrieval,evidence chain construction,truthfulness assessment,and report generation,thereby establishing a closed-loop mechanism of"Coordination-Specialization-Integration"Experimental results on benchmark fact-checking datasets demonstrate that the proposed framework achieves competitive performance in both veracity classification accuracy and fact-checking report generation quality,substantially enhancing the credibility of fact-checking results.关键词
虚假信息/事实核查/多智能体/证据链/大语言模型Key words
Misinformation/Fact-checking/Multi-agent Systems/Evidence Chain/Large Language Models分类
信息技术与安全科学引用本文复制引用
相甍甍,纪泽旭,郭佳鸣,王秀琨..证据链增强的多智能体分组讨论事实核查框架研究[J].数字图书馆论坛,2026,22(5):20-33,14.基金项目
本研究得到国家社会科学基金一般项目"认知和心理账户视角下社交媒体用户隐私悖论行为及干预机制研究"(编号:21BTQ057)资助. （编号:21BTQ057）
