@inproceedings{zerong-etal-2025-systematic,
    title = "A Systematic Survey of Claim Verification: Corpora, Systems, and Case Studies",
    author = "Zerong, Zhaxi  and
      Li, Chenxi  and
      Liu, Xinyi  and
      Chen, Ju-hui  and
      Xia, Fei",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.findings-emnlp.1170/",
    doi = "10.18653/v1/2025.findings-emnlp.1170",
    pages = "21452--21474",
    ISBN = "979-8-89176-335-7",
    abstract = "Automated Claim Verification (CV){---}the task of assessing a claim{'}s veracity against explicitly provided evidence{---}is a critical tool in the fight against growing misinformation. This survey offers a comprehensive analysis of 198 studies published between January 2022 and March 2025, synthesizing recent advances in CV corpus creation and system design. Through two in-depth case studies, we illuminate persistent challenges in veracity annotation, limitations of conventional CV pipelines, and pitfalls in recent claim decomposition approaches. We conclude by identifying key unresolved challenges and proposing productive directions for future research."
}