---
title: "Who cites Retrieval-Augmented Generation — 93 citing papers"
description: "93 papers of the Elamur Research library cite «Retrieval-Augmented Generation for AI-Generated Content: A Survey», found in their…"
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# Who cites «Retrieval-Augmented Generation for AI-Generated Content: A Survey»

93 papers of our library cite it (of the 149,439 whose bibliographies we read) · 29 with a page here, the most cited first · [← back to «Retrieval-Augmented Generation for AI-Generated Content: A Survey»](https://md.research.elamur.ai/free/en/papers/zhao-2024-retrieval-augmented-generation-ai-generated/)

1. **[A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/fan-2024-survey-rag-meeting-llms-towards/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Wenqi Fan; Yujuan Ding; Liangbo Ning; Shijie Wang; Hengyun Li; Dawei Yin; Tat-Seng Chua;, Qing Li*2024 · 1,010 citations*
2. [**LightRAG: Simple and Fast Retrieval-Augmented Generation arXiv:2410.05779**Zirui Guo, Lianghao Xia, Yanhua Yu, et al.*2024 · 316 citations*](https://md.research.elamur.ai/free/en/papers/guo-2024-lightrag-simple-fast-retrieval-augmented/)
3. **[Graph Retrieval-Augmented Generation: A Survey](https://md.research.elamur.ai/free/en/papers/peng-2024-graph-retrieval-augmented-generation-survey/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Boci Peng, Yun Zhu, Yongchao Liu, et al.*2024 · 276 citations*
4. **[Tool Learning with Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/qu-2024-tool-learning-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Changle Qu, Sunhao Dai, Xiaochi Wei, et al.*2024 · 195 citations*
5. **[Searching for Best Practices in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2024-searching-best-practices-retrieval-augmented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaohua Wang, Zhenghua Wang, Xuan Gao, et al.*2024 · 150 citations*
6. [**Can LLM-Generated Misinformation Be Detected? arXiv:2309.13788**Canyu Chen, Kai Shu*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-llm-generated-misinformation-detected/)
7. [**Large language models for education: A survey and outlook**Wang*2024 · 101 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-large-language-models-education-survey/)
8. [**LLM Inference Unveiled: Survey and Roofline Model Insights arXiv 2024**Zhihang Yuan, Yuzhang Shang, Yang Zhou, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2024-llm-inference-unveiled-survey-roofline/)
9. [**Retrieval-Augmented Generation with Graphs (GraphRAG) arXiv:2501.00309**Haoyu Han, Yu Wang, Harry Shomer, et al.*2025 · 87 citations*](https://md.research.elamur.ai/free/en/papers/han-2025-retrieval-augmented-generation-graphs-graphrag/)
10. **[Retrieval-Augmented Generation for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/wu-2024-retrieval-augmented-generation-natural-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Shangyu Wu, Ying Xiong, Yufei Cui, et al.*2024 · 86 citations*
11. **[WebThinker: Empowering Large Reasoning Models with Deep Research Capability](https://md.research.elamur.ai/free/en/papers/li-2025-webthinker-empowering-large-reasoning-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoxi Li, Jiajie Jin, Guanting Dong, et al.*2025 · 72 citations*
12. **[Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2024-buffer-thoughts-thought-augmented-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ling Yang, Zhaochen Yu, Tianjun Zhang, et al.*2024 · 67 citations*
13. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
14. **[MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing](https://md.research.elamur.ai/free/en/papers/niu-2026-mineru2-5-decoupled-vision-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junbo Niu, Zheng Liu, Zhuangcheng Gu, et al.*2026 · 35 citations*
15. **[Pandora's Box or Aladdin's Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2025-pandora-s-box-or-aladdin/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinyang Wu, Shuai Zhang, Feihu Che, et al.*2025 · 19 citations*
16. **[StepSearch: Igniting LLMs Search Ability via Step-Wise Proximal Policy Optimization](https://md.research.elamur.ai/free/en/papers/zheng-2025-stepsearch-igniting-llms-search-ability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuhui Zheng, Kang An, Ziliang Wang, et al.*2025 · 19 citations*
17. [**Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models arXiv:2411.02382**Guangzhi Xiong, Eric Xie, Amir Hassan Shariatmadari, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2024-improving-scientific-hypothesis-generation-knowledge/)
18. [**How Much Can RAG Help the Reasoning of LLM? arXiv:2410.02338**Jingyu Liu, Jiaen Lin, Yong Liu*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-much-rag-help-reasoning-llm/)
19. **[Progressive Multimodal Reasoning via Active Retrieval](https://md.research.elamur.ai/free/en/papers/dong-2025-progressive-multimodal-reasoning-active-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanting Dong, Chenghao Zhang, Mengjie Deng, et al.*2025 · 10 citations*
20. **[TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-templaterl-structured-template-guided-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyang Wu, Chonghua Liao, Mingkuan Feng, et al.*2026 · 8 citations*
21. **[GLARE: Agentic Reasoning for Legal Judgment Prediction](https://md.research.elamur.ai/free/en/papers/yang-2026-glare-agentic-reasoning-legal-judgment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Yang, Chenlong Deng, Zhicheng Dou*2026 · 5 citations*
22. [**MÖVE: A Holistic LLM Benchmark for the German Public Sector arXiv:2606.13111**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-m-ove-holistic-llm-benchmark/)
23. **[Building Common Ground in Dialogue: A Survey](https://md.research.elamur.ai/free/en/papers/anikina-2025-building-common-ground-dialogue-survey/) [LUHME Workshop](https://md.research.elamur.ai/free/en/venues/luhme/)**Tatiana Anikina, Alina Leippert, Simon Ostermann*2025 · 1 citation*
24. **[BubbleRAG: Interactive Cognitive Offloading with Thought Bubble in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-bubblerag-interactive-cognitive-offloading-thought/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fuda Ye, Jiachuan Wang, Yongqi Zhang, et al.*2026*
25. **[Chart-MRAG: Benchmarking Multimodal Retrieval Augmented Generation on Chart-based Documents](https://md.research.elamur.ai/free/en/papers/ymyang-2026-chart-mrag-benchmarking-multimodal-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ymyang, Jiang Zhong, Li Jin, et al.*2026*
26. **[Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/wang-2026-enhancing-llm-based-search-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junzhe Wang, Zhiheng Xi, Yajie Yang, et al.*2026*
27. **[Evidence-Augmented Generation Reasoning for Extremely Low-Resource Language Decipherment](https://md.research.elamur.ai/free/en/papers/zhu-2026-evidence-augmented-generation-reasoning-extremely/) [Workshop on Multilinguality in the Era of Large Language Models](https://md.research.elamur.ai/free/en/venues/mellm/)**Xiaoyu Zhu, Long Yuan, Rui Qi, et al.*2026*
28. **[How to Make LMs Strong Node Classifiers?](https://md.research.elamur.ai/free/en/papers/xu-2026-how-make-lms-strong-node/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhe Xu, Kaveh Hassani, Si Zhang, et al.*2026*
29. **[Survey on Application of Retrieval-augmented Generation in Software Engineering (检索增强生成在软件工程中的应用综述)](https://md.research.elamur.ai/free/en/papers/zhang-2025-application-retrieval-augmented/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Quanjun Zhang (张犬俊), Yang Xie (谢杨), Chunrong Fang (房春荣), et al.*2025*

64 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/zhao-2024-retrieval-augmented-generation-ai-generated/) — Retrieval-Augmented Generation for AI-Generated Content: A Survey