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BOE-XSUM: Extreme Summarization in Clear Language of Spanish Legal Decrees and Notifications

September 29, 2025
Authors: Andrés Fernández García, Javier de la Rosa, Julio Gonzalo, Roser Morante, Enrique Amigó, Alejandro Benito-Santos, Jorge Carrillo-de-Albornoz, Víctor Fresno, Adrian Ghajari, Guillermo Marco, Laura Plaza, Eva Sánchez Salido
cs.AI

Abstract

The ability to summarize long documents succinctly is increasingly important in daily life due to information overload, yet there is a notable lack of such summaries for Spanish documents in general, and in the legal domain in particular. In this work, we present BOE-XSUM, a curated dataset comprising 3,648 concise, plain-language summaries of documents sourced from Spain's ``Bolet\'{\i}n Oficial del Estado'' (BOE), the State Official Gazette. Each entry in the dataset includes a short summary, the original text, and its document type label. We evaluate the performance of medium-sized large language models (LLMs) fine-tuned on BOE-XSUM, comparing them to general-purpose generative models in a zero-shot setting. Results show that fine-tuned models significantly outperform their non-specialized counterparts. Notably, the best-performing model -- BERTIN GPT-J 6B (32-bit precision) -- achieves a 24\% performance gain over the top zero-shot model, DeepSeek-R1 (accuracies of 41.6\% vs.\ 33.5\%).

PDF11September 30, 2025