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SourceMinds system generates fact-checking articles with citation auditing

Researchers have developed a multi-agent system called SourceMinds for the CLEF 2026 CheckThat! Lab, designed to generate comprehensive fact-checking articles. The pipeline integrates evidence retrieval, structured planning, article generation, and a crucial NLI-based citation auditing step. This system aims to ensure that generated articles are well-supported by evidence and accurately cite their sources, addressing challenges in automated fact-checking. AI

IMPACT This system advances automated fact-checking by improving evidence grounding and citation accuracy in generated articles.

RANK_REASON The cluster contains a research paper detailing a new system for fact-checking article generation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

SourceMinds system generates fact-checking articles with citation auditing

COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Farhan Sharukh Hasan, Anirban Saha Anik, Eric Liu, Xiaoying Song, Mohotarema Rashid, Lingzi Hong ·

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

    arXiv:2607.24802v1 Announce Type: cross 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 combin…