This paper describes VILLAIN, a multimodal fact-checking system that verifies image-text claims through prompt-based multi-agent collaboration. For the AVerImaTeC shared task, VILLAIN employs vision-language model agents across multiple stages of fact-checking. Textual and visual evidence is retrieved from the knowledge store enriched through additional web collection. To identify key information and address inconsistencies among evidence items, modality-specific and cross-modal agents generate analysis reports. In the subsequent stage, question-answer pairs are produced based on these reports. Finally, the Verdict Prediction agent produces the verification outcome based on the image-text claim and the generated question-answer pairs. Our system ranked first on the leaderboard across all evaluation metrics. The source code is publicly available at https://github.com/ssu-humane/VILLAIN.
@article{arxiv.2602.04587,
title = {VILLAIN at AVerImaTeC: Verifying Image-Text Claims via Multi-Agent Collaboration},
author = {Jaeyoon Jung and Yejun Yoon and Kunwoo Park},
journal= {arXiv preprint arXiv:2602.04587},
year = {2026}
}
Comments
A system description paper for the AVerImaTeC shared task at the Ninth FEVER Workshop (co-located with EACL 2026)