activity
20242026
collaborators

7 papers

cs.CL2026

Omnilingual SONAR: Cross-Lingual and Cross-Modal Sentence Embeddings Bridging Massively Multilingual Text and Speech

Omnilingual SONAR Team, João Maria Janeiro, Pere-Lluís Huguet Cabot +17

Cross-lingual sentence encoders typically cover only a few hundred languages and often trade downstream quality for stronger alignment, limiting their adoption. We introduce OmniSO…

cs.CL2026

Omnilingual MT: Machine Translation for 1,600 Languages

Omnilingual MT Team, Belen Alastruey, Niyati Bafna +29

High-quality machine translation (MT) can scale to hundreds of languages, setting a high bar for multilingual systems. However, compared to the world's 7,000 languages, current sys…

cs.CL2025

Translate, then Detect: Leveraging Machine Translation for Cross-Lingual Toxicity Classification

Samuel J. Bell, Eduardo Sánchez, David Dale +3

Multilingual toxicity detection remains a significant challenge due to the scarcity of training data and resources for many languages. While prior work has leveraged the translate-…

cs.CL2025

LCFO: Long Context and Long Form Output Dataset and Benchmarking

Marta R. Costa-jussÃ, Pierre Andrews, Mariano Coria Meglioli +10

This paper presents the Long Context and Form Output (LCFO) benchmark, a novel evaluation framework for assessing gradual summarization and summary expansion capabilities across di…

cs.CL2025

BOUQuET: dataset, Benchmark and Open initiative for Universal Quality Evaluation in Translation

The Omnilingual MT Team, Pierre Andrews, Mikel Artetxe +14

BOUQuET is a multi-way, multicentric and multi-register/domain dataset and benchmark, and a broader collaborative initiative. This dataset is handcrafted in 8 non-English languages…

cs.CL2025

Improving Language and Modality Transfer in Translation by Character-level Modeling

Ioannis Tsiamas, David Dale, Marta R. Costa-jussÃ

Current translation systems, despite being highly multilingual, cover only 5% of the world's languages. Expanding language coverage to the long-tail of low-resource languages requi…