Papers by Timur Garipov
BERT-like Models for Slavic Morpheme Segmentation (2025.acl-long)
Copied to clipboard
| Challenge: | Existing morpheme segmentation algorithms for Slavic languages have been improved but performance is still low for words with roots not present in training data. |
| Approach: | They propose to fine-tune BERT-like models for morpheme segmentation using data from Belarusian, Czech, and Russian to account for word semantics. |
| Outcome: | The proposed models outperform all previous approaches in Czech and Russian, with word-level accuracy of 92.5-95.1%. |