AINeutralarXiv – CS AI · 5h ago6/10
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Fine-Tuning LLMs for Report Summarization: Analysis on Supervised and Unsupervised Data
Researchers demonstrate that fine-tuning Large Language Models for report summarization is feasible on limited on-premise hardware (1-2 A100 GPUs), addressing practical constraints in sensitive government and intelligence applications. The study compares supervised and unsupervised approaches, finding that fine-tuning improves summary quality and reduces invalid outputs, even without ground-truth training data.