[Submitted on 30 Jul 2026]
Abstract:Misinformation spreads faster than professional fact-checkers can manually verify it and write articles explaining their verdicts. This creates a need to automate the production of fact-checking articles. This paper details work done by the DS@GT ARC team for CLEF 2026 CheckThat! Lab Task 3 Fact-Checking Article Generation. We seek to generate a full fact-checking article from a claim, its original verdict, and a set of scraped source documents. Our team built a four-stage pipeline that cleans noisy evidence, retrieves and clusters relevant sources, generates the article by conditioning texttt{Llama-3.1-8B-Instruct} on the original fact-checker verdict, and recovers inline citations through deterministic post-processing. We achieved a mean score of 0.428 and ranked 3rd out of 9 teams for the CLEF 2026 CheckThat! Lab Task 3, compared to a baseline mean score of 0.272. Our code is available on GitHub at this https URL.
Submission history
From: Hoang Thanh Thanh Truong [view email]
[v1] Thu, 30 Jul 2026 04:20:07 UTC (133 KB)
