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cs.CL2026
Hit-RAG: Learning to Reason with Long Contexts via Preference Alignment
Junming Liu, Yuqi Li, Shiping Wen +2
Despite the promise of Retrieval-Augmented Generation in grounding Multimodal Large Language Models with external knowledge, the transition to extensive contexts often leads to sig…
cs.CL2025
From Ranking to Selection: A Simple but Efficient Dynamic Passage Selector for Retrieval Augmented Generation
Siyuan Meng, Junming Liu, Yirong Chen +5
Retrieval-augmented generation (RAG) systems are often bottlenecked by their reranking modules, which typically score passages independently and select a fixed Top-K size. This app…
cs.CL2025★ 1 cited
HM-RAG: Hierarchical Multi-Agent Multimodal Retrieval Augmented Generation
Pei Liu, Xin Liu, Ruoyu Yao +4
While Retrieval-Augmented Generation (RAG) augments Large Language Models (LLMs) with external knowledge, conventional single-agent RAG remains fundamentally limited in resolving c…