collaborators

6 papers

cs.CL2026

Towards Reliable Multilingual LLMs-as-a-Judge: An Empirical Study

Irune Zubiaga, Aitor Soroa, Rodrigo Agerri

Large language models (LLMs) are increasingly used for the automatic evaluation of generated text, yet most prior work focuses on English. Despite the growing demand for multilingu…

cs.CL2026

Multilingual Medical Reasoning for Question Answering with Large Language Models

Pietro Ferrazzi, Aitor Soroa, Rodrigo Agerri

Large Language Models (LLMs) with reasoning capabilities have recently demonstrated strong potential in medical Question Answering (QA). Existing approaches are largely English-foc…

cs.CL2026

BERnaT: Basque Encoders for Representing Natural Textual Diversity

Ekhi Azurmendi, Joseba Fernandez de Landa, Jaione Bengoetxea +5

Language models depend on massive text corpora that are often filtered for quality, a process that can unintentionally exclude non-standard linguistic varieties, reduce model robus…

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.CL2026

Conditioning LLMs to Generate Code-Switched Text

Maite Heredia, Gorka Labaka, Jeremy Barnes +1

Code-switching (CS) is still a critical challenge in Natural Language Processing (NLP), due to the limited availability of large-scale, diverse CS datasets for robust training and…

cs.CL2025

EuskañolDS: A Naturally Sourced Corpus for Basque-Spanish Code-Switching

Maite Heredia, Jeremy Barnes, Aitor Soroa

Code-switching (CS) remains a significant challenge in Natural Language Processing (NLP), mainly due a lack of relevant data. In the context of the contact between the Basque and S…