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cs.CL2026
IE as Cache: Information Extraction Enhanced Agentic Reasoning
Hang Lv, Sheng Liang, Hongchao Gu +5
Information Extraction aims to distill structured, decision-relevant information from unstructured text, serving as a foundation for downstream understanding and reasoning. However…
cs.CL2026
Tackling the Inherent Difficulty of Noise Filtering in RAG
Jingyu Liu, Jiaen Lin, Yong Liu
Retrieval-Augmented Generation (RAG) has become a widely adopted approach to enhance Large Language Models (LLMs) by incorporating external knowledge and reducing hallucinations. H…
cs.CL2024★ 1 cited
How Much Can RAG Help the Reasoning of LLM?
Jingyu Liu, Jiaen Lin, Yong Liu
Retrieval-Augmented Generation (RAG) has gained significant popularity in modern Large Language Models (LLMs) due to its effectiveness in introducing new knowledge and reducing hal…