collaborators

7 papers

cs.CL2026

Cross-lingual Self-Consistency for Multilingual Reasoning with Language Models

Ahmed Elhady, Eneko Agirre, Mikel Artetxe

Despite expanding their multilingual coverage, the advanced reasoning capabilities of LLMs remain largely confined to a few high-resource languages like English. To address this, w…

cs.CL2026

Instructing Large Language Models for Low-Resource Languages: A Systematic Study for Basque

Oscar Sainz, Naiara Perez, Julen Etxaniz +9

Instructing language models with user intent requires large instruction datasets, which are only available for a limited set of languages. In this paper, we explore alternatives to…

cs.CV2026

Towards Artwork Explanation in Large-scale Vision Language Models

Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2

Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…

cs.CL2025

Emergent Abilities of Large Language Models under Continued Pretraining for Language Adaptation

Ahmed Elhady, Eneko Agirre, Mikel Artetxe

Continued pretraining (CPT) is a popular approach to adapt existing large language models (LLMs) to new languages. When doing so, it is common practice to include a portion of Engl…

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

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…