Mehmet Selman Baysan

TR-MTEB: A Comprehensive Benchmark and Embedding Model Suite for Turkish Sentence Representations

We introduce TR-MTEB, the first large-scale, task-diverse benchmark designed to evaluate sentence embedding models for Turkish. Covering six core tasks as classification, clustering, pair classification, retrieval, bitext mining, and semantic textual similarity, TR-MTEB incorporates 26 high-quality