版权材料对大型语言模型的影响：挪威视角

The Impact of Copyrighted Material on Large Language Models: A Norwegian Perspective

December 12, 2024

作者: Javier de la Rosa, Vladislav Mikhailov, Lemei Zhang, Freddy Wetjen, David Samuel, Peng Liu, Rolv-Arild Braaten, Petter Mæhlum, Magnus Breder Birkenes, Andrey Kutuzov, Tita Enstad, Svein Arne Brygfjeld, Jon Atle Gulla, Stephan Oepen, Erik Velldal, Wilfred Østgulen, Liljia Øvrelid, Aslak Sira Myhre

cs.AI

摘要

在训练生成语言模型时使用受版权保护的材料引发了重要的法律和伦理问题。本文提出了一个框架，并通过实证评估受版权材料对挪威大型语言模型（LLMs）性能的影响的结果。我们发现，当模型在多样化的挪威基准上进行评估时，书籍和报纸都对模型有积极贡献，而虚构作品可能会导致性能下降。我们的实验可以为那些作品对AI发展有贡献的作者制定一种补偿方案提供信息。

English

The use of copyrighted materials in training generative language models raises critical legal and ethical questions. This paper presents a framework for and the results of empirically assessing the impact of copyrighted materials on the performance of large language models (LLMs) for Norwegian. We found that both books and newspapers contribute positively when the models are evaluated on a diverse set of Norwegian benchmarks, while fiction works possibly lead to decreased performance. Our experiments could inform the creation of a compensation scheme for authors whose works contribute to AI development.