4 papers
LangMAP: A Language-Adaptive Approach to Tokenization
Clara Meister, Suchir Salhan, Andrzej Szablewski +3
Language-specific tokenizers improve tokenization quality and the downstream performance of models on those languages. However, using such a tokenizer comes at a cost: either a new…
What Language is This? Ask Your Tokenizer
Clara Meister, Ahmetcan Yavuz, Pietro Lesci +1
Language Identification (LID) is an important component of many multilingual natural language processing pipelines, where it facilitates corpus curation, training data analysis, an…
Causal Estimation of Tokenisation Bias
Pietro Lesci, Clara Meister, Thomas Hofmann +2
Modern language models are typically trained over subword sequences, but ultimately define probabilities over character-strings. Ideally, the choice of the tokeniser -- which maps…
Self-Training Large Language Models for Tool-Use Without Demonstrations
Ne Luo, Aryo Pradipta Gema, Xuanli He +3
Large language models (LLMs) remain prone to factual inaccuracies and computational errors, including hallucinations and mistakes in mathematical reasoning. Recent work augmented L…