@inproceedings{straka-2025-corpipe,
    title = "{C}or{P}ipe at {CRAC} 2025: Evaluating Multilingual Encoders for Multilingual Coreference Resolution",
    author = "Straka, Milan",
    editor = "Ogrodniczuk, Maciej  and
      Novak, Michal  and
      Poesio, Massimo  and
      Pradhan, Sameer  and
      Ng, Vincent",
    booktitle = "Proceedings of the Eighth Workshop on Computational Models of Reference, Anaphora and Coreference",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.crac-1.11/",
    doi = "10.18653/v1/2025.crac-1.11",
    pages = "130--139",
    abstract = "We present CorPipe 25, the winning entry to the CRAC 2025 Shared Task on Multilingual Coreference Resolution. This fourth iteration of the shared task introduces a new LLM track alongside the original unconstrained track, features reduced development and test sets to lower computational requirements, and includes additional datasets. CorPipe 25 represents a complete reimplementation of our previous systems, migrating from TensorFlow to PyTorch. Our system significantly outperforms all other submissions in both the LLM and unconstrained tracks by a substantial margin of 8 percentage points. The source code and trained models are publicly available at https://github.com/ufal/crac2025-corpipe."
}