CorPipe at CRAC 2025: Evaluating Multilingual Encoders for Multilingual Coreference Resolution

Milan Straka
9/22/2025
cs.CL

Official code: ufal/crac2025-corpipe (8 stars, MPL-2.0, last commit 2026-01-30).

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.

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Code Implementations(1)

MPL-2.0

CorPipe 25: CRAC 2025 Winning System for Multilingual Coreference Resolution

80Shell, PythonAug 3, 20258 months agoMPL-2.0

Cite this paper

@article{straka2025corpipe,
  title  = {CorPipe at CRAC 2025: Evaluating Multilingual Encoders for Multilingual Coreference Resolution},
  author = {Milan Straka},
  year   = {2025},
  eprint = {2509.17858},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2509.17858v2}
}

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