{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/infact-a-strong-baseline-for-automated-fact","title":"InFact: A Strong Baseline for Automated Fact-Checking","arxiv_id":null,"date":"2024-11-01","proceeding":"- 2024 11","authors":["Mark Rothermel","Tobias Braun","Marcus Rohrbach","Anna Rohrbach"],"abstract":"The spread of disinformation poses a global threat to democratic societies, necessitating robust and scalable Automated Fact-Checking (AFC) systems. The AVeriTeC Shared Task Challenge 2024 offers a realistic benchmark for text-based fact-checking methods. This paper presents Information-Retrieving Fact-Checker (InFact), an LLM-based approach that breaks down the task of claim verification into a 6-stage process, including evidence retrieval. When using GPT-4o as the backbone, InFact achieves an AVeriTeC score of 63% on the test set, outperforming all other 20 teams competing in the challenge, and establishing a new strong baseline for future text-only AFC systems. Qualitative analysis of mislabeled instances reveals that InFact often yields a more accurate conclusion than AVeriTeC’s human-annotated ground truth.","url_abs":"https://aclanthology.org/2024.fever-1.12/","url_pdf":"https://aclanthology.org/2024.fever-1.12.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"claim-verification","task_name":"Claim Verification"},{"task_slug":"fact-checking","task_name":"Fact Checking"},{"task_slug":"retrieval","task_name":"Retrieval"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/fact-checking-on-averitec","task":"Fact Checking","dataset":"AVeriTeC","model":"InFact","rank_in_archive_order":3,"of":3,"metrics":{"AveriTeC":"0.63","Question + Answer score":"0.34","Question Only score":"0.45"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}