arXiv:2509.17858

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

Published on Sep 22

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Abstract

CorPipe 25, a multilingual coreference resolution system, outperforms other submissions in both LLM and unconstrained tracks by 8 percentage points using PyTorch.

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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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