4 citations · 10 across the 7 of their papers we have counts for
7 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. Using one with an existing pretrained model requires either t…
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…
Causal Estimation of Memorisation Profiles
Pietro Lesci, Clara Meister, Thomas Hofmann +2
Understanding memorisation in language models has practical and societal implications, e.g., studying models' training dynamics or preventing copyright infringements. Prior work de…
AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets
Pietro Lesci, Andreas Vlachos
Active learning for imbalanced classification tasks is challenging as the minority classes naturally occur rarely. Gathering a large pool of unlabelled data is thus essential to ca…
Diable: Efficient Dialogue State Tracking as Operations on Tables
Pietro Lesci, Yoshinari Fujinuma, Momchil Hardalov +3
Sequence-to-sequence state-of-the-art systems for dialogue state tracking (DST) use the full dialogue history as input, represent the current state as a list with all the slots, an…