Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training
Large language models are increasingly capable in general, but their utility can remain modest in niche or understudied areas. One approach to address this limitation is to specialise existing models through additional training on target-domain corpora. In this work, we investigate such continued pre-training for adapting large language models to Swedish journalism, using a high-quality dataset that we curate from millions of news articles. To evaluate the adaptation efficacy, we also construct a novel domain-specific benchmark that covers six editorial tasks. Through full and parameter-effici
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- LinkedLinked via arxiv author · 85%Lukas Borggren →
“Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training”
- LinkedLinked via arxiv author · 85%Jenny Kunz →
“Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training”
- LinkedLinked via arxiv author · 85%Marco Kuhlmann →
“Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training”