Fine-tuned mT5-large outperforms prompt-based LLMs on Czech anaphora resolution (88% vs 74.5% accuracy) on a new dataset derived from the Prague Dependency Treebank.
In: Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguisticsfor Cultural Heritage,Social Sciences,Hu- manities and Literature (LaTeCH-CLfL 2024)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Evaluating Prompt-Based and Fine-Tuned Approaches to Czech Anaphora Resolution
Fine-tuned mT5-large outperforms prompt-based LLMs on Czech anaphora resolution (88% vs 74.5% accuracy) on a new dataset derived from the Prague Dependency Treebank.