InFact: A Strong Baseline for Automated Fact-Checking
Mark Rothermel, Tobias Braun, Marcus Rohrbach, Anna Rohrbach · 2024
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 humanannotated ground truth.