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Jan Ebert

2 accepted papers

2024

Investigating Multilingual Instruction-Tuning: Do Polyglot Models Demand for Multilingual Instructions?

EMNLP 2024main

The adaption of multilingual pre-trained LLMs into eloquent and helpful assistants is essential to facilitate their use across different language regions. In that spirit, we are the first to conduct an extensive study of the performance of multilingual models instruction-tuned on different language…

2024

Tokenizer Choice For LLM Training: Negligible or Crucial?

NAACL 2024findings

The recent success of large language models (LLMs) has been predominantly driven by curating the training dataset composition, scaling of model architectures and dataset sizes and advancements in pretraining objectives, leaving tokenizer influence as a blind spot.Shedding light on this underexplored…