84 citations · 100 across the 9 of their papers we have counts for
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cs.AI2025
RAG-Anything: All-in-One RAG Framework
Zirui Guo, Xubin Ren, Lingrui Xu +2
Retrieval-Augmented Generation (RAG) has emerged as a fundamental paradigm for expanding Large Language Models beyond their static training limitations. However, a critical misalig…
cs.AI2025★ 1 cited
MiniRAG: Towards Extremely Simple Retrieval-Augmented Generation
Tianyu Fan, Jingyuan Wang, Xubin Ren +1
The growing demand for efficient and lightweight Retrieval-Augmented Generation (RAG) systems has highlighted significant challenges when deploying Small Language Models (SLMs) in…