1 citations · 1 across the 11 of their papers we have counts for
12 papers
CRITICS - Critical Science Without Borders: Language Models to Promote Critical Thinking in Science Education
Rodrigo Agerri, Itziar Aldabe, Elena Cabrio +10
The CRITICS project addresses science accessibility and literacy by converging advanced Machine Translation (MT) based on Large Language Models (LLMs) with educational technology.…
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…
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…
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…
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…
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…
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…
A LLM-Based Ranking Method for the Evaluation of Automatic Counter-Narrative Generation
Irune Zubiaga, Aitor Soroa, Rodrigo Agerri
This paper proposes a novel approach to evaluate Counter Narrative (CN) generation using a Large Language Model (LLM) as an evaluator. We show that traditional automatic metrics co…
BertaQA: How Much Do Language Models Know About Local Culture?
Julen Etxaniz, Gorka Azkune, Aitor Soroa +2
Large Language Models (LLMs) exhibit extensive knowledge about the world, but most evaluations have been limited to global or anglocentric subjects. This raises the question of how…
XNLIeu: a dataset for cross-lingual NLI in Basque
Maite Heredia, Julen Etxaniz, Muitze Zulaika +3
XNLI is a popular Natural Language Inference (NLI) benchmark widely used to evaluate cross-lingual Natural Language Understanding (NLU) capabilities across languages. In this paper…
Latxa: An Open Language Model and Evaluation Suite for Basque
Julen Etxaniz, Oscar Sainz, Naiara Perez +6
We introduce Latxa, a family of large language models for Basque ranging from 7 to 70 billion parameters. Latxa is based on Llama 2, which we continue pretraining on a new Basque c…
Improving Explicit Spatial Relationships in Text-to-Image Generation through an Automatically Derived Dataset
Ander Salaberria, Gorka Azkune, Oier Lopez de Lacalle +3
Existing work has observed that current text-to-image systems do not accurately reflect explicit spatial relations between objects such as 'left of' or 'below'. We hypothesize that…