5 papers · 1 filter
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,…
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…
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…
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…
Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain
Iker GarcÃa-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…