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cs.CL2025
Achieving Tokenizer Flexibility in Language Models through Heuristic Adaptation and Supertoken Learning
Shaurya Sharthak, Vinayak Pahalwan, Adithya Kamath +1
Pretrained language models (LLMs) are often constrained by their fixed tokenization schemes, leading to inefficiencies and performance limitations, particularly for multilingual or…
cs.CL2024
From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language Representation
Artur Kiulian, Anton Polishko, Mykola Khandoga +4
In the rapidly advancing field of AI and NLP, generative large language models (LLMs) stand at the forefront of innovation, showcasing unparalleled abilities in text understanding…