papers

Publications (6)

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.CL2026

HPLT 3.0: Very Large-Scale Multilingual Resources for LLMs and MT. Mono- and Bi-lingual Data, Multilingual Evaluation, and Pre-Trained Models

Stephan Oepen, Nikolay Arefev, Mikko Aulamo +29

We present an ongoing initiative to provide open, very large, high-quality, and richly annotated textual datasets for almost 200 languages. At 30 trillion tokens, this is likely th…

cs.CL2026

CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data

Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett +94

Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heter…

cs.CL2024

Context and System Fusion in Post-ASR Emotion Recognition with Large Language Models

Pavel Stepachev, Pinzhen Chen, Barry Haddow

Large language models (LLMs) have started to play a vital role in modelling speech and text. To explore the best use of context and multiple systems' outputs for post-ASR speech em…

cs.CL2024

Quality or Quantity? On Data Scale and Diversity in Adapting Large Language Models for Low-Resource Translation

Vivek Iyer, Bhavitvya Malik, Pavel Stepachev +3

Despite the recent popularity of Large Language Models (LLMs) in Machine Translation (MT), their performance in low-resource languages (LRLs) still lags significantly behind Neural…

cs.CL2025

An Expanded Massive Multilingual Dataset for High-Performance Language Technologies (HPLT)

Laurie Burchell, Ona de Gibert, Nikolay Arefyev +32

Training state-of-the-art large language models requires vast amounts of clean and diverse textual data. However, building suitable multilingual datasets remains a challenge. In th…