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Turkish MMLU Pro: Traceable Option Augmentation and Its Validity Limits in Turkish Multiple-Choice Evaluation
M. Ali Bayram
Adding answer options can lower multiple-choice scores without improving assessment validity. Turkish MMLU Pro examines this distinction using 12,000 Turkish-source questions acros…
Adapting Multilingual Embedding Models to Turkish via Cross-Lingual Tokenizer Surgery and Offline Distillation
M. Ali Bayram, Banu Diri, Savaş Yıldırım
Sentence embeddings are a foundational component for semantic search, clustering, classification, and retrieval-augmented generation. This paper presents embeddingmagibu-200m, a Tu…
Doğal Dil İşlemede Tokenizasyon Standartları ve Ölçümü: Türkçe Üzerinden Büyük Dil Modellerinin Karşılaştırmalı Analizi
M. Ali Bayram, Ali Arda Fincan, Ahmet Semih Gümüş +3
Tokenization is a fundamental preprocessing step in Natural Language Processing (NLP), significantly impacting the capability of large language models (LLMs) to capture linguistic…
Büyük Dil Modelleri için TR-MMLU Benchmarkı: Performans Değerlendirmesi, Zorluklar ve İyileştirme Fırsatları
M. Ali Bayram, Ali Arda Fincan, Ahmet Semih Gümüş +3
Language models have made significant advancements in understanding and generating human language, achieving remarkable success in various applications. However, evaluating these m…
Tokens with Meaning: A Hybrid Tokenization Approach for Turkish
M. Ali Bayram, Ali Arda Fincan, Ahmet Semih Gümüş +4
Tokenization shapes how language models perceive morphology and meaning in NLP, yet widely used frequency-driven subword tokenizers (e.g., Byte Pair Encoding and WordPiece) can fra…
Tokenization Standards for Linguistic Integrity: Turkish as a Benchmark
M. Ali Bayram, Ali Arda Fincan, Ahmet Semih Gümüş +3
Tokenization is a fundamental preprocessing step in NLP, directly impacting large language models' (LLMs) ability to capture syntactic, morphosyntactic, and semantic structures. Th…