Knowledge Tree
Relations (1)
cross_type 3.17 — strongly supporting 8 facts
arXiv serves as the primary repository for numerous research papers that introduce, survey, or evaluate Retrieval-Augmented Generation (RAG) frameworks and methodologies, as evidenced by the publications cited in [1], [2], [3], [4], [5], [6], [7], and [8].
Facts (8)
Sources
KG-IRAG: A Knowledge Graph-Based Iterative Retrieval-Augmented ... arxiv.org 3 facts
referenceYuzhe Zhang, Yipeng Zhang, Yidong Gan, Lina Yao, and Chen Wang authored the paper 'Causal graph discovery with retrieval-augmented generation based large language models', published as arXiv preprint arXiv:2402.15301 in 2024.
referenceHao Yu, Aoran Gan, Kai Zhang, Shiwei Tong, Qi Liu, and Zhaofeng Liu authored the paper 'Evaluation of retrieval-augmented generation: A survey', published as arXiv preprint arXiv:2405.07437 in 2024.
referencePenghao Zhao, Hailin Zhang, Qinhan Yu, Zhengren Wang, Yunteng Geng, Fangcheng Fu, Ling Yang, Wentao Zhang, and Bin Cui authored the paper 'Retrieval-augmented generation for ai-generated content: A survey', published as arXiv preprint arXiv:2402.19473 in 2024.
LLM-KG4QA: Large Language Models and Knowledge Graphs for ... github.com 2 facts
referenceThe paper 'mmRAG: A Modular Benchmark for Retrieval-Augmented Generation over Text, Tables, and Knowledge Graphs' (arXiv, 2025) introduces a modular benchmark for evaluating retrieval-augmented generation across text, tables, and knowledge graphs.
referenceThe paper 'MiniRAG: Towards Extremely Simple Retrieval-Augmented Generation' (arXiv, 2025) by LiHua-World proposes a simplified approach to retrieval-augmented generation.
Bridging the Gap Between LLMs and Evolving Medical Knowledge arxiv.org 1 fact
referenceXuejiao Zhao et al. (2025) published 'Medrag: Enhancing retrieval-augmented generation with knowledge graph-elicited reasoning for healthcare copilot' as an arXiv preprint (arXiv:2502.04413), which focuses on improving RAG with knowledge graphs.
LLM Hallucination Detection and Mitigation: State of the Art in 2026 zylos.ai 1 fact
referenceThe paper 'RAGAS: Automated Evaluation of RAG,' published on arXiv, introduces RAGAS as a framework for the automated evaluation of retrieval-augmented generation systems.
Knowledge Graph Combined with Retrieval-Augmented Generation ... drpress.org 1 fact
referenceHe et al. introduced G-retriever, a retrieval-augmented generation framework for textual graph understanding and question answering, in an arXiv preprint in 2024.