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This paper introduces SEEK, a framework for semantic evidence extraction in multilingual fact verification, which constructs coherent evidence chunks from full articles and fine-tunes multilingual LLMs with LoRA, achieving up to 20% improvement in macro-F1 over baselines.
This paper introduces PrimeFacts, a methodology and resource for extracting fine-grained evidence from fact-checking articles using large language models. The extracted premises improve evidence retrieval and claim verification performance by up to 30% in MRR and 10-20 points in Macro-F1.