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Retrieval-Augmented Generation (RAG) has emerged as a powerful framework to overcome the knowledge limitations of Large Language Models (LLMs) by integrating external retrieval with language generation.
The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al · 2009
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Proximal policy optimization algorithms, 2017
John Schulman, Filip Wolski, et al · 2017
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, et al · 2020
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Self-rag: Learning to retrieve, generate, and critique through self-reflection, 2023
Akari Asai, Zeqiu Wu, et al · 2023
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Function calling and other api updates, June 2023
Atty Eleti, Jeff Harris, et al · 2023
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Retrieval-augmented generation for large language models: A survey
Yunfan Gao, Yun Xiong, et al · 2023
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Fine-grained late-interaction multi-modal retrieval for retrieval augmented visual question answering
Weizhe Lin, Jinghong Chen, et al · 2023
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Ra-dit: Retrieval-augmented dual instruction tuning
Xi Victoria Lin, Xilun Chen, et al · 2023
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Query rewriting in retrieval-augmented large language models
Xinbei Ma, Yeyun Gong, et al · 2023
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Measuring and narrowing the compositionality gap in language models, 2023
Ofir Press, Muru Zhang, et al · 2023
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The troubling emergence of hallucination in large language models-an extensive definition, quantification, and prescriptive remediations
Vipula Rawte, Swagata Chakraborty, et al · 2023
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Tptu: Task planning and tool usage of large language model-based ai agents
Jingqing Ruan, Yihong Chen, et al · 2023
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Exploring language models: A comprehensive survey and analysis
Aditi Singh · 2023
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Chain-of-thought prompting elicits reasoning in large language models, 2023
Jason Wei, Xuezhi Wang, et al · 2023
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React: Synergizing reasoning and acting in language models, 2023
Shunyu Yao, Jeffrey Zhao, et al · 2023
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Siren’s song in the ai ocean: a survey on hallucination in large language models
Yue Zhang, Yafu Li, et al · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, et al · 2023
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Benchmarking large language models in retrieval-augmented generation
Jiawei Chen, Hongyu Lin, et al · 2024
Cited alongside, same era.
Modular rag: Transforming rag systems into lego-like reconfigurable frameworks, 2024
Yunfan Gao, Yun Xiong, et al · 2024
Cited alongside, same era.
Adaptive-rag: Learning to adapt retrieval-augmented large language models through question complexity, 2024
Soyeong Jeong, Jinheon Baek, et al · 2024
Cited alongside, same era.
Tptu-v2: Boosting task planning and tool usage of large language model-based agents in real-world industry systems
Yilun Kong, Jingqing Ruan, et al · 2024
Cited alongside, same era.
Jiarui Li, Ye Yuan, et al · 2024
Cited alongside, same era.
Controlling large language model-based agents for large-scale decision-making: An actor-critic approach
Bin Zhang, Hangyu Mao, et al · 2024
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Retrieval-augmented generation for ai-generated content: A survey
Penghao Zhao, Hailin Zhang, et al · 2024
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Are large language models good statisticians?
Yizhang Zhu, Shiyin Du, et al · 2024
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Rezero: Enhancing llm search ability by trying one-more-time, 2025
Alan Dao and Thinh Le · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025
DeepSeek-AI, Daya Guo, et al · 2025
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Retrieval augmented generation or long-context llms? a comprehensive study and hybrid approach, 2024
Zhuowan Li, Cheng Li, et al · 2024
Cited alongside, same era.
Zi-Ao Ma, Tian Lan, et al · 2024
Cited alongside, same era.
Openai o1 system card, 2024
OpenAI, :, et al · 2024
Cited alongside, same era.
Agentic retrieval-augmented generation for time series analysis
Chidaksh Ravuru, Sagar Srinivas Sakhinana, et al · 2024
Cited alongside, same era.
Raptor: Recursive abstractive processing for tree-organized retrieval, 2024
Parth Sarthi, Salman Abdullah, et al · 2024
Cited alongside, same era.
Deepseekmath: Pushing the limits of mathematical reasoning in open language models, 2024
Zhihong Shao, Peiyi Wang, et al · 2024
Cited alongside, same era.
Adaptive retrieval-augmented generation for conversational systems, 2024
Xi Wang, Procheta Sen, et al · 2024
Cited alongside, same era.
Mcts-rag: Enhancing retrieval-augmented generation with monte carlo tree search, 2025
Yunhai Hu, Yilun Zhao, et al · 2025
Closest in time.
A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions
Lei Huang, Weijiang Yu, et al · 2025
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Deepretrieval: Hacking real search engines and retrievers with large language models via reinforcement learning, 2025
Pengcheng Jiang, Jiacheng Lin, et al · 2025
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Search-r1: Training llms to reason and leverage search engines with reinforcement learning, 2025
Bowen Jin, Hansi Zeng, et al · 2025
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Search-o1: Agentic search-enhanced large reasoning models, 2025
Xiaoxi Li, Guanting Dong, et al · 2025
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From system 1 to system 2: A survey of reasoning large language models
Zhong-Zhi Li, Duzhen Zhang, et al · 2025
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Deep research system card, February 2025
OpenAI · 2025
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R1-searcher: Incentivizing the search capability in llms via reinforcement learning, 2025
Huatong Song, Jinhao Jiang, et al · 2025
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Retrieval-augmented generation with conflicting evidence
Han Wang, Archiki Prasad, et al · 2025
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Mramg-bench: A beyondtext benchmark for multimodal retrieval-augmented multimodal generation
Qinhan Yu, Zhiyou Xiao, et al · 2025
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Deepresearcher: Scaling deep research via reinforcement learning in real-world environments, 2025
Yuxiang Zheng, Dayuan Fu, et al · 2025
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