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Retrieval-augmented generation have become central in natural language processing due to their efficacy in generating factual content.
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FEVER: a Large-scale Dataset for Fact Extraction and VERification. In NAACL-HLT . Association for Computational Linguistics, 809–819
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Natural Questions: a Benchmark for Question Answering Research
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Language Models are Few-Shot Learners. In NeurIPS
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REALM: Retrieval-Augmented Language Model Pre-Training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020 · 2020
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Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps. In COLING . International Committee on Computational Linguistics, 6609–6625
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SpanBERT: Improving Pre-training by Representing and Predicting Spans
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Dense Passage Retrieval for Open-Domain Question Answering. In EMNLP (1) . Association for Computational Linguistics, 6769–6781
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Generalization through Memorization: Nearest Neighbor Language Models. In ICLR . OpenReview.net
Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2020 · 2020
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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, et al · 2020
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Efficient Nearest Neighbor Language Models. In EMNLP (1) . Association for Computational Linguistics, 5703–5714
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Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering. In EACL . Association for Computational Linguistics, 874–880
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Webgpt: Browser-assisted question-answering with human feedback
Text Embeddings by Weakly-Supervised Contrastive Pre-training
Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, and Furu Wei. 2022 · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022 · 2022
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Training Language Models with Memory Augmentation. In EMNLP . Association for Computational Linguistics, 5657–5673
Zexuan Zhong, Tao Lei, and Danqi Chen. 2022 · 2022
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Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al · 2021
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Detecting Hallucinated Content in Conditional Neural Sequence Generation. In ACL/IJCNLP (Findings) (Findings of ACL) , Vol. ACL/IJCNLP 2021. Association for Computational Linguistics, 1393–1404
Chunting Zhou, Graham Neubig, Jiatao Gu, Mona T. Diab, Francisco Guzmán, Luke Zettlemoyer, and Marjan Ghazvininejad. 2021 · 2021
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Improving Language Models by Retrieving from Trillions of Tokens. In ICML (Proceedings of Machine Learning Research) , Vol. 162. PMLR, 2206–2240
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George van den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, Diego de Las Casas, Aurelia Guy, Jacob Menick, Roman Ring, Tom Hennigan, Saffron Huang, Loren Maggiore, Chris Jones, Albin Cassirer, Andy Brock, Michela Paganini, Geoffrey Irving, Oriol Vinyals, Simon Osindero, Karen Simonyan, Jack W. Rae, Erich Elsen, and Laurent Sifre. 2022 · 2022
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GLM: General Language Model Pretraining with Autoregressive Blank Infilling. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 320–335
Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang. 2022 · 2022
Cited alongside, same era.
TRUE: Re-evaluating Factual Consistency Evaluation. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . Association for Computational Linguistics, Seattle, United States, 3905–3920
Or Honovich, Roee Aharoni, Jonathan Herzig, Hagai Taitelbaum, Doron Kukliansy, Vered Cohen, Thomas Scialom, Idan Szpektor, Avinatan Hassidim, and Yossi Matias. 2022 · 2022
Cited alongside, same era.
Few-shot Learning with Retrieval Augmented Language Models
Gautier Izacard, Patrick S. H. Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, and Edouard Grave. 2022 · 2022
Cited alongside, same era.
Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer. In EMNLP . Association for Computational Linguistics, 2336–2349
Zhengbao Jiang, Luyu Gao, Zhiruo Wang, Jun Araki, Haibo Ding, Jamie Callan, and Graham Neubig. 2022 · 2022
Cited alongside, same era.
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
Omar Khattab, Keshav Santhanam, Xiang Lisa Li, David Hall, Percy Liang, Christopher Potts, and Matei Zaharia. 2022 · 2022
Cited alongside, same era.
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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Decomposed Prompting: A Modular Approach for Solving Complex Tasks. In ICLR . OpenReview.net
Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, and Ashish Sabharwal. 2023 · 2023
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Xiaoxi Li, Yujia Zhou, and Zhicheng Dou. 2023 · 2023
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In-Context Retrieval-Augmented Language Models
Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, and Yoav Shoham. 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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REPLUG: Retrieval-Augmented Black-Box Language Models
Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, Mike Lewis, Luke Zettlemoyer, and Wen-tau Yih. 2023 · 2023
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Reflexion: Language agents with verbal reinforcement learning
Noah Shinn, Federico Cassano, Beck Labash, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2023 · 2023
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Llama 2: Open Foundation and Fine-Tuned Chat Models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi …, and Thomas Scialom. 2023 · 2023
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Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions. In ACL (1) . Association for Computational Linguistics, 10014–10037
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. 2023 · 2023
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Metacognitive Prompting Improves Understanding in Large Language Models
Yuqing Wang and Yun Zhao. 2023 · 2023
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