activity
20232026
most citedGoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction

17 citations · 32 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Merge and Conquer: Instructing Multilingual Models by Adding Target Language Weights

Eneko Valero, Maria Ribalta i Albado, Oscar Sainz +2

Large Language Models (LLMs) remain heavily centered on English, with limited performance in low-resource languages. Existing adaptation approaches, such as continual pre-training,…

cs.CL2026

SemBench: A Universal Semantic Framework for LLM Evaluation

Mikel Zubillaga, Naiara Perez, Oscar Sainz +1

Recent progress in Natural Language Processing (NLP) has been driven by the emergence of Large Language Models (LLMs), which exhibit remarkable generative and reasoning capabilitie…

cs.CL2025

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.CL2024★ 12 cited

Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain

Iker García-Ferrero, Rodrigo Agerri, Aitziber Atutxa Salazar +10

Research on language technology for the development of medical applications is currently a hot topic in Natural Language Understanding and Generation. Thus, a number of large langu…

cs.CL2024

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…

cs.CL2023★ 3 cited

This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models

Iker García-Ferrero, Begoña Altuna, Javier Álvez +2

Although large language models (LLMs) have apparently acquired a certain level of grammatical knowledge and the ability to make generalizations, they fail to interpret negation, a…

cs.CL2023★ 17 cited

GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction

Oscar Sainz, Iker García-Ferrero, Rodrigo Agerri +3

Large Language Models (LLMs) combined with instruction tuning have made significant progress when generalizing to unseen tasks. However, they have been less successful in Informati…