4 citations · 5 across the 6 of their papers we have counts for
6 papers · 1 filter
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…
Setting Standards in Turkish NLP: TR-MMLU for Large Language Model Evaluation
M. Ali Bayram, Ali Arda Fincan, Ahmet Semih Gümüş +3
Language models have made remarkable advancements in understanding and generating human language, achieving notable success across a wide array of applications. However, evaluating…