Tag
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.
Proposes a query-adaptive semantic chunking method for retrieval-augmented generation that dynamically adjusts chunk boundaries using contextual window expansion to improve retrieval precision.