Papers by Mehmet Selman Baysan
TR-MTEB: A Comprehensive Benchmark and Embedding Model Suite for Turkish Sentence Representations (2025.findings-emnlp)
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| Challenge: | TR-MTEB is the first large-scale, task-diverse benchmark for sentence embedding models for Turkish. |
| Approach: | a new benchmark evaluates sentence embedding models for Turkish . TR-MTEB covers six core tasks and 26 high-quality datasets . |
| Outcome: | The TR-MTEB benchmark covers six core tasks and includes 26 high-quality datasets . the models achieve competitive performance across most tasks and significantly improve on baseline models. |