@inproceedings{cao-etal-2026-automatic,
    title = "The Automatic Verification of Image-Text Claims ({AV}er{I}ma{T}e{C}) Shared Task",
    author = "Cao, Rui  and
      Chen, Yulong  and
      Deng, Zhenyun  and
      Schlichtkrull, Michael  and
      Vlachos, Andreas",
    editor = "Akhtar, Mubashara  and
      Aly, Rami  and
      Cao, Rui  and
      Christodoulopoulos, Christos  and
      Cocarascu, Oana  and
      Guo, Zhijiang  and
      Mittal, Arpit  and
      Schlichtkrull, Michael  and
      Thorne, James  and
      Vlachos, Andreas",
    booktitle = "Proceedings of the Ninth Fact Extraction and {VER}ification Workshop ({FEVER})",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/port-ingestion-scripts/2026.fever-1.6/",
    pages = "74--90",
    ISBN = "979-8-89176-365-4",
    abstract = "The Automatic Verification of Image-Text Claims (AVerImaTeC) shared task aims to advance system development for retrieving evidence and verifying real-world image-text claims. Participants were allowed to either employ external knowledge sources, such as web search engines, or leverage the curated knowledge store provided by the organizers. System performance was evaluated using the AVerImaTeC score, defined as a conditional verdict accuracy in which a verdict is considered correct only when the associated evidence score exceeds a predefined threshold. The shared task attracted 14 submissions during the development phase and 6 submissions during the testing phase. All participating systems in the testing phase outperformed the baseline provided. The winning team, HUMAN, achieved an AVerImaTeC score of 0.5455. This paper provides a detailed description of the shared task, presents the complete evaluation results, and discusses key insights and lessons learned."
}