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Recent breakthroughs in large language models (LLMs), particularly in reasoning capabilities, have propelled Retrieval-Augmented Generation (RAG) to unprecedented levels.
The web as a knowledge-base for answering complex questions
Alon Talmor and Jonathan Berant. 2018 · 2018
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Natural questions: a benchmark for question answering research
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Constructing a multi-hop qa dataset for comprehensive evaluation of reasoning steps
Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, and Akiko Aizawa. 2020 · 2020
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KILT: a benchmark for knowledge intensive language tasks
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Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. 2022a · 2022
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MuSiQue: Multihop Questions via Single-hop Question Composition
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. 2022b · 2022
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Self-rag: Learning to retrieve, generate, and critique through self-reflection. In The Twelfth International Conference on Learning Representations
Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi. 2023 · 2023
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Theoremqa: A theorem-driven question answering dataset
Wenhu Chen, Ming Yin, Max Ku, Pan Lu, Yixin Wan, Xueguang Ma, Jianyu Xu, Xinyi Wang, and Tony Xia. 2023 · 2023
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Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2023 · 2023
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Retrieval-augmented generation for large language models: A survey
Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, and Haofen Wang. 2023 · 2023
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Active retrieval augmented generation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 7969–7992
Zhengbao Jiang, Frank F Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, and Graham Neubig. 2023 · 2023
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Let’s verify step by step. In The Twelfth International Conference on Learning Representations
Hunter Lightman, Vineet Kosaraju, Yuri Burda, Harrison Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, and Karl Cobbe. 2023 · 2023
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Query rewriting in retrieval-augmented large language models. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 5303–5315
Xinbei Ma, Yeyun Gong, Pengcheng He, Hai Zhao, and Nan Duan. 2023 · 2023
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Gaia: a benchmark for general ai assistants. In The Twelfth International Conference on Learning Representations
Grégoire Mialon, Clémentine Fourrier, Thomas Wolf, Yann LeCun, and Thomas Scialom. 2023 · 2023
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Enhancing retrieval-augmented large language models with iterative retrieval-generation synergy
Zhihong Shao, Yeyun Gong, Yelong Shen, Minlie Huang, Nan Duan, and Weizhu Chen. 2023 · 2023
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Freshllms: Refreshing large language models with search engine augmentation
Tu Vu, Mohit Iyyer, Xuezhi Wang, Noah Constant, Jerry Wei, Jason Wei, Chris Tar, Yun-Hsuan Sung, Denny Zhou, Quoc Le, et al · 2023
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Cmb: A comprehensive medical benchmark in chinese
Xidong Wang, Guiming Hardy Chen, Dingjie Song, Zhiyi Zhang, Zhihong Chen, Qingying Xiao, Feng Jiang, Jianquan Li, Xiang Wan, Benyou Wang, et al · 2023
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Do not think that much for 2+ 3=? on the overthinking of o1-like llms
Xingyu Chen, Jiahao Xu, Tian Liang, Zhiwei He, Jianhui Pang, Dian Yu, Linfeng Song, Qiuzhi Liu, Mengfei Zhou, Zhuosheng Zhang, et al · 2024
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Unified active retrieval for retrieval augmented generation
Qinyuan Cheng, Xiaonan Li, Shimin Li, Qin Zhu, Zhangyue Yin, Yunfan Shao, Linyang Li, Tianxiang Sun, Hang Yan, and Xipeng Qiu. 2024 · 2024
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From local to global: A graph rag approach to query-focused summarization
Darren Edge, Ha Trinh, Newman Cheng, Joshua Bradley, Alex Chao, Apurva Mody, Steven Truitt, Dasha Metropolitansky, Robert Osazuwa Ness, and Jonathan Larson. 2024 · 2024
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SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback
Jingsheng Gao, Linxu Li, Weiyuan Li, Yuzhuo Fu, and Bin Dai. 2024a · 2024
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Modular rag: Transforming rag systems into lego-like reconfigurable frameworks
Yunfan Gao, Yun Xiong, Meng Wang, and Haofen Wang. 2024b · 2024
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Lightrag: Simple and fast retrieval-augmented generation
Zirui Guo, Lianghao Xia, Yanhua Yu, Tu Ao, and Chao Huang. 2024 · 2024
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Chaoqun He, Renjie Luo, Yuzhuo Bai, Shengding Hu, Zhen Leng Thai, Junhao Shen, Jinyi Hu, Xu Han, Yujie Huang, Yuxiang Zhang, et al · 2024
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BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval. In The Thirteenth International Conference on Learning Representations
SU Hongjin, Howard Yen, Mengzhou Xia, Weijia Shi, Niklas Muennighoff, Han-yu Wang, Liu Haisu, Quan Shi, Zachary S Siegel, Michael Tang, et al · 2024
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Grounding by trying: Llms with reinforcement learning-enhanced retrieval
Sheryl Hsu, Omar Khattab, Chelsea Finn, and Archit Sharma. 2024 · 2024
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Agents’ Room: Narrative Generation through Multi-step Collaboration
Fantine Huot, Reinald Kim Amplayo, Jennimaria Palomaki, Alice Shoshana Jakobovits, Elizabeth Clark, and Mirella Lapata. 2024 · 2024
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Open-rag: Enhanced retrieval-augmented reasoning with open-source large language models
Shayekh Bin Islam, Md Asib Rahman, KSM Hossain, Enamul Hoque, Shafiq Joty, and Md Rizwan Parvez. 2024 · 2024
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Aaron Jaech, Adam Kalai, Adam Lerer, Adam Richardson, Ahmed El-Kishky, Aiden Low, Alec Helyar, Aleksander Madry, Alex Beutel, Alex Carney, et al · 2024
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Livecodebench: Holistic and contamination free evaluation of large language models for code
Naman Jain, King Han, Alex Gu, Wen-Ding Li, Fanjia Yan, Tianjun Zhang, Sida Wang, Armando Solar-Lezama, Koushik Sen, and Ion Stoica. 2024 · 2024
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Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, and Jong C Park. 2024 · 2024
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Yucheng Jiang, Yijia Shao, Dekun Ma, Sina J Semnani, and Monica S Lam. 2024a · 2024
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Yucheng Jiang, Yijia Shao, Dekun Ma, Sina J Semnani, and Monica S Lam. 2024b · 2024
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REAPER: Reasoning based retrieval planning for complex RAG systems. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management . 4621–4628
Ashutosh Joshi, Sheikh Muhammad Sarwar, Samarth Varshney, Sreyashi Nag, Shrivats Agrawal, and Juhi Naik. 2024 · 2024
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PlanRAG: A plan-then-retrieval augmented generation for generative large language models as decision makers. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) . 6537–6555
Myeonghwa Lee, Seonho An, and Min-Soo Kim. 2024 · 2024
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An Agent Framework for Real-Time Financial Information Searching with Large Language Models
Jinzheng Li, Jingshu Zhang, Hongguang Li, and Yiqing Shen. 2024c · 2024
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Xingxuan Li, Weiwen Xu, Ruochen Zhao, Fangkai Jiao, Shafiq Joty, and Lidong Bing. 2024a · 2024
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Xingxuan Li, Weiwen Xu, Ruochen Zhao, Fangkai Jiao, Shafiq Joty, and Lidong Bing. 2024b · 2024
Cited alongside, same era.
Medcot: Medical chain of thought via hierarchical expert
Jiaxiang Liu, Yuan Wang, Jiawei Du, Joey Tianyi Zhou, and Zuozhu Liu. 2024 · 2024
Cited alongside, same era.
Shengjie Ma, Chengjin Xu, Xuhui Jiang, Muzhi Li, Huaren Qu, Cehao Yang, Jiaxin Mao, and Jian Guo. 2024 · 2024
Cited alongside, same era.
Gorilla: Large language model connected with massive apis
Shishir G Patil, Tianjun Zhang, Xin Wang, and Joseph E Gonzalez. 2024 · 2024
Cited alongside, same era.
Gpqa: A graduate-level google-proof q&a benchmark. In First Conference on Language Modeling
Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?
Yancheng He, Shilong Li, Jiaheng Liu, Weixun Wang, Xingyuan Bu, Ge Zhang, Zhongyuan Peng, Zhaoxiang Zhang, Zhicheng Zheng, Wenbo Su, et al · 2025
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FG-RAG: Enhancing Query-Focused Summarization with Context-Aware Fine-Grained Graph RAG
Yubin Hong, Chaofan Li, Jingyi Zhang, and Yingxia Shao. 2025 · 2025
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REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models
Jian Hu. 2025 · 2025
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MCTS-RAG: Enhancing Retrieval-Augmented Generation with Monte Carlo Tree Search
Yunhai Hu, Yilun Zhao, Chen Zhao, and Arman Cohan. 2025 · 2025
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DeepRetrieval: Powerful Query Generation for Information Retrieval with Reinforcement Learning
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David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R Bowman. 2024 · 2024
Cited alongside, same era.
Deepseekmath: Pushing the limits of mathematical reasoning in open language models
Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu, Junxiao Song, Xiao Bi, Haowei Zhang, Mingchuan Zhang, YK Li, Y Wu, et al · 2024
Cited alongside, same era.
Can Language Models Solve Olympiad Programming?
Quan Shi, Michael Tang, Karthik Narasimhan, and Shunyu Yao. 2024a · 2024
Cited alongside, same era.
Can Language Models Solve Olympiad Programming?
Quan Shi, Michael Tang, Karthik Narasimhan, and Shunyu Yao. 2024b · 2024
Cited alongside, same era.
RARE: Retrieval-Augmented Reasoning Enhancement for Large Language Models
Hieu Tran, Zonghai Yao, Junda Wang, Yifan Zhang, Zhichao Yang, and Hong Yu. 2024 · 2024
Cited alongside, same era.
Retriever-and-Memory: Towards Adaptive Note-Enhanced Retrieval-Augmented Generation
Ruobing Wang, Daren Zha, Shi Yu, Qingfei Zhao, Yuxuan Chen, Yixuan Wang, Shuo Wang, Yukun Yan, Zhenghao Liu, Xu Han, et al · 2024
Cited alongside, same era.
Domainrag: A chinese benchmark for evaluating domain-specific retrieval-augmented generation
Shuting Wang, Jiongnan Liu, Shiren Song, Jiehan Cheng, Yuqi Fu, Peidong Guo, Kun Fang, Yutao Zhu, and Zhicheng Dou. 2024c · 2024
Cited alongside, same era.
Searching for best practices in retrieval-augmented generation
Xiaohua Wang, Zhenghua Wang, Xuan Gao, Feiran Zhang, Yixin Wu, Zhibo Xu, Tianyuan Shi, Zhengyuan Wang, Shizheng Li, Qi Qian, et al · 2024
Cited alongside, same era.
Pengcheng Jiang. 2025 · 2025
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Zhicheng Lee, Shulin Cao, Jinxin Liu, Jiajie Zhang, Weichuan Liu, Xiaoyin Che, Lei Hou, and Juanzi Li. 2025 · 2025
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Search-o1: Agentic search-enhanced large reasoning models
Xiaoxi Li, Guanting Dong, Jiajie Jin, Yuyao Zhang, Yujia Zhou, Yutao Zhu, Peitian Zhang, and Zhicheng Dou. 2025a · 2025
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Zhuoqun Li, Haiyang Yu, Xuanang Chen, Hongyu Lin, Yaojie Lu, Fei Huang, Xianpei Han, Yongbin Li, and Le Sun. 2025b · 2025
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Elias Lumer, Pradeep Honaganahalli Basavaraju, Myles Mason, James A Burke, and Vamse Kumar Subbiah. 2025 · 2025
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KBQA-o1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search
Haoran Luo, Yikai Guo, Qika Lin, Xiaobao Wu, Xinyu Mu, Wenhao Liu, Meina Song, Yifan Zhu, Luu Anh Tuan, et al · 2025
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Crud-rag: A comprehensive chinese benchmark for retrieval-augmented generation of large language models
Yuanjie Lyu, Zhiyu Li, Simin Niu, Feiyu Xiong, Bo Tang, Wenjin Wang, Hao Wu, Huanyong Liu, Tong Xu, and Enhong Chen. 2025 · 2025
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Niklas Muennighoff, Zitong Yang, Weijia Shi, Xiang Lisa Li, Li Fei-Fei, Hannaneh Hajishirzi, Luke Zettlemoyer, Percy Liang, Emmanuel Candès, and Tatsunori Hashimoto. 2025 · 2025
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Insight-RAG: Enhancing LLMs with Insight-Driven Augmentation
Pouya Pezeshkpour and Estevam Hruschka. 2025 · 2025
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R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
Huatong Song, Jinhao Jiang, Yingqian Min, Jie Chen, Zhipeng Chen, Wayne Xin Zhao, Lei Fang, and Ji-Rong Wen. 2025 · 2025
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Sakhinana Sagar Srinivas and Venkataramana Runkana. 2025 · 2025
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Stop overthinking: A survey on efficient reasoning for large language models
Yang Sui, Yu-Neng Chuang, Guanchu Wang, Jiamu Zhang, Tianyi Zhang, Jiayi Yuan, Hongyi Liu, Andrew Wen, Hanjie Chen, Xia Hu, et al · 2025
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ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding
Zhongxiang Sun, Qipeng Wang, Weijie Yu, Xiaoxue Zang, Kai Zheng, Jun Xu, Xiao Zhang, Song Yang, and Han Li. 2025 · 2025
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Ante Wang, Linfeng Song, Ye Tian, Dian Yu, Haitao Mi, Xiangyu Duan, Zhaopeng Tu, Jinsong Su, and Dong Yu. 2025c · 2025
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PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation
Jinyu Wang, Jingjing Fu, Rui Wang, Lei Song, and Jiang Bian. 2025b · 2025
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Chain-of-Retrieval Augmented Generation
Liang Wang, Haonan Chen, Nan Yang, Xiaolong Huang, Zhicheng Dou, and Furu Wei. 2025a · 2025
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RARE: Retrieval-Augmented Reasoning Modeling
Zhengren Wang, Jiayang Yu, Dongsheng Ma, Zhe Chen, Yu Wang, Zhiyu Li, Feiyu Xiong, Yanfeng Wang, Linpeng Tang, Wentao Zhang, et al · 2025
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Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research
Junde Wu, Jiayuan Zhu, and Yuyuan Liu. 2025b · 2025
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Graph-augmented reasoning: Evolving step-by-step knowledge graph retrieval for llm reasoning
Wenjie Wu, Yongcheng Jing, Yingjie Wang, Wenbin Hu, and Dacheng Tao. 2025a · 2025
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OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking
Zekun Xi, Wenbiao Yin, Jizhan Fang, Jialong Wu, Runnan Fang, Ningyu Zhang, Jiang Yong, Pengjun Xie, Fei Huang, and Huajun Chen. 2025 · 2025
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Retrieval-Augmented Generation by Evidence Retroactivity in LLMs
Liang Xiao, Wen Dai, Shuai Chen, Bin Qin, Chongyang Shi, Haopeng Jing, and Tianyu Guo. 2025 · 2025
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Rag-gym: Optimizing reasoning and search agents with process supervision
Guangzhi Xiong, Qiao Jin, Xiao Wang, Yin Fang, Haolin Liu, Yifan Yang, Fangyuan Chen, Zhixing Song, Dengyu Wang, Minjia Zhang, et al · 2025
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MCTS-KBQA: Monte Carlo Tree Search for Knowledge Base Question Answering
Guanming Xiong, Haochen Li, and Wen Zhao. 2025c · 2025
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Ruibin Xiong, Yimeng Chen, Dmitrii Khizbullin, and Jürgen Schmidhuber. 2025a · 2025
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Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Fengli Xu, Qianyue Hao, Zefang Zong, Jingwei Wang, Yunke Zhang, Jingyi Wang, Xiaochong Lan, Jiahui Gong, Tianjian Ouyang, Fanjin Meng, et al · 2025
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O1 embedder: Let retrievers think before action
Ruiran Yan, Zheng Liu, and Defu Lian. 2025 · 2025
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Zhuocheng Zhang, Yang Feng, and Min Zhang. 2025 · 2025
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Xuejiao Zhao, Siyan Liu, Su-Yin Yang, and Chunyan Miao. 2025 · 2025
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DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments
Yuxiang Zheng, Dayuan Fu, Xiangkun Hu, Xiaojie Cai, Lyumanshan Ye, Pengrui Lu, and Pengfei Liu. 2025 · 2025
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Meta-PKE: Memory-Enhanced Task-Adaptive Personal Knowledge Extraction in Daily Life
Yijie Zhong, Feifan Wu, Mengying Guo, Xiaolian Zhang, Meng Wang, and Haofen Wang. 2025 · 2025
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Retrieval-Augmented Process Reward Model for Generalizable Mathematical Reasoning
Jiachen Zhu, Congmin Zheng, Jianghao Lin, Kounianhua Du, Ying Wen, Yong Yu, Jun Wang, and Weinan Zhang. 2025b · 2025
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Mitigating Lost-in-Retrieval Problems in Retrieval Augmented Multi-Hop Question Answering
Rongzhi Zhu, Xiangyu Liu, Zequn Sun, Yiwei Wang, and Wei Hu. 2025a · 2025
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