SourceMinds at CheckThat! 2026: NLI-Grounded Citation Auditing in a Multi-Agent Pipeline for Full Fact-Checking Article Generation

2026-07-06

AI Summary

This work addresses the challenge of automatically generating fact-checking articles grounded in verifiable citations by leveraging claims, veracity labels, and supporting evidence documents. To this end, the authors propose a multi-agent collaborative pipeline that integrates dense retrieval, source-balanced evidence selection, structured content planning, and citation-aware generation. The framework innovatively incorporates a gated self-evaluation mechanism and a natural language inference (NLI)-driven citation auditing module to repair missing citations and automatically eliminate redundant or unsupported references. Experimental results demonstrate that the proposed approach significantly improves citation accuracy and source credibility in the generated articles, thereby validating the effectiveness of jointly optimizing evidence selection, structured generation, and post-hoc citation verification.

Abstract

This paper presents our system for Task 3 of the CLEF 2026 CheckThat! Lab, which focuses on generating full fact-checking articles from claims, veracity labels, and evidence documents. We propose a multi-agent pipeline that combines evidence retrieval, structured fact planning, article generation, gated self-critique, and NLI-based citation auditing. The system retrieves claim-relevant evidence using dense retrieval, reranking, and source-balanced selection, then generates a citation-supported article from a structured plan. A gated self-critique stage revises weakly grounded drafts, while the NLI citation auditor repairs missing citations and removes unsupported or redundant ones. The approach highlights the importance of combining evidence selection, structured generation, and post-generation citation validation for source-grounded fact-checking article generation.

Problem

• fact-checking article generation
• citation auditing
• evidence grounding
• natural language inference
• source attribution

Innovation

• multi-agent pipeline
• NLI-based citation auditing
• structured fact planning
• gated self-critique
• source-grounded generation