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Retrieval Augmented Generation (RAG) has become the standard approach for equipping Large Language Models (LLMs) with up-to-date knowledge.
Making sense of sensemaking 1: Alternative perspectives
Gary Klein, Brian Moon, and Robert R. Hoffman. 2006 · 2006
Earlier work this paper cites.
Making new memories: the role of the hippocampus in new associative learning
Wendy A. Suzuki. 2007 · 2007
Earlier work this paper cites.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018 · 2018
Earlier work this paper cites.
Learning to retrieve reasoning paths over wikipedia graph for question answering
Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, Richard Socher, and Caiming Xiong. 2020 · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
Earlier work this paper cites.
Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020 · 2020
Earlier work this paper cites.
Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2022 · 2022
Cited alongside, same era.
Large dual encoders are generalizable retrievers
Jianmo Ni, Chen Qu, Jing Lu, Zhuyun Dai, Gustavo Hernandez Abrego, Ji Ma, Vincent Zhao, Yi Luan, Keith Hall, Ming-Wei Chang, and Yinfei Yang. 2022 · 2022
Cited alongside, same era.
When not to trust language models: Investigating effectiveness of parametric and non-parametric memories
Alex Mallen, Akari Asai, Victor Zhong, Rajarshi Das, Daniel Khashabi, and Hannaneh Hajishirzi. 2023 · 2023
Cited alongside, same era.
End-to-end beam retrieval for multi-hop question answering
Jiahao Zhang, Haiyang Zhang, Dongmei Zhang, Yong Liu, and Shen Huang. 2023 · 2023
Cited alongside, same era.
Llama 3 model card
AI@Meta. 2024 · 2024
Cited alongside, same era.
From local to global: A graph rag approach to query-focused summarization
Derek Edge, Hoang Trinh, Nicholas Cheng, Joshua Bradley, Allen Chao, Ajay Mody, Shayne Truitt, and Jason Larson. 2024 · 2024
Later among the works it cites.
Model editing harms general abilities of large language models: Regularization to the rescue
Jia-Chen Gu, Hao-Xiang Xu, Jia-Yu Ma, Pu Lu, Zheng-Hua Ling, Kai-Wei Chang, and Nanyun Peng. 2024 · 2024
Later among the works it cites.
Retrieve, summarize, plan: Advancing multi-hop question answering with an iterative approach
Zhouyu Jiang, Mengshu Sun, Lei Liang, and Zhiqiang Zhang. 2024 · 2024
Later among the works it cites.
Raptor: Recursive abstractive processing for tree-organized retrieval
Priyanka Sarthi, Sameer Abdullah, Abhilash Tuli, Sakshi Khanna, Abhijit Goldie, and Christopher D. Manning. 2024 · 2024
Later among the works it cites.
Rear: A relevance-aware retrieval-augmented framework for open-domain question answering
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Dense x retrieval: What retrieval granularity should we use?
Tong Chen, Hongwei Wang, Sihao Chen, Wenhao Yu, Kaixin Ma, Xinran Zhao, Hongming Zhang, and Dong Yu. 2024 · 2024
Cited alongside, same era.
Evaluating the ripple effects of knowledge editing in language models
Roni Cohen, Eran Biran, Ori Yoran, Amir Globerson, and Mor Geva. 2024 · 2024
Cited alongside, same era.
Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. 2022a
Cited in the paper.
Musique: Multihop questions via single-hop question composition
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. 2022b
Cited in the paper.
Yuhao Wang, Ruiyang Ren, Junyi Li, Wayne Xin Zhao, Jing Liu, and Ji-Rong Wen. 2024 · 2024
Later among the works it cites.
From rag to memory: Non-parametric continual learning for large language models
Bernal Jiménez Gutiérrez, Yiheng Shu, Weijian Qi, Sizhe Zhou, and Yu Su. 2025 · 2025
Closest in time.
Nv-embed-v2: Improved techniques for training llms as generalist embedding models
Chang-Bin Lee, Rishav Roy, Mengjiao Xu, Jonathan Raiman, Mohammad Shoeybi, Bryan Catanzaro, and Wei Ping. 2025 · 2025
Closest in time.