collaborators

9 papers

cs.CL2026

Explicit Boundary Markers for Subword Vocabularies

Sander Land, Clara Meister

Subword tokenizers represent many common words twice in space-using writing systems, once with a leading space and once without. The two entries have separate embeddings in models,…

cs.CL2026

Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization

Negar Foroutan, Clara Meister, Debjit Paul +4

Tokenization is the first -- and often least scrutinized -- step of most NLP pipelines. Standard algorithms for learning tokenizers rely on frequency-based objectives, which favor…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2025

Back to Bytes: Revisiting Tokenization Through UTF-8

Amit Moryossef, Clara Meister, Pavel Stepachev +1

We present UTF8Tokenizer, a minimalist byte-level tokenizer that maps text exactly to IDs corresponding to the bytes underlying the text's UTF-8 encoding (e.g., byte x09 is token I…

cs.CL2025

Locally Typical Sampling

Clara Meister, Tiago Pimentel, Gian Wiher +1

Today's probabilistic language generators fall short when it comes to producing coherent and fluent text despite the fact that the underlying models perform well under standard met…