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Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources, enabling more accurate and contextually relevant responses tailored to user queries.
ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Approximate nearest neighbor negative contrastive learning for dense text retrieval
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, and Arnold Overwijk. 2020 · 2007
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A human generated machine reading comprehension dataset
P Bajaj, D Campos, N Craswell, L Deng, J Gao, X Liu, R Majumder, A McNamara, B Mitra, T Nguyen, and 1 others. 2018 · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin. 2018 · 2018
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Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning. 2018 · 2018
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Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, and 1 others. 2019 · 2019
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Retrieval augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang. 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, and 1 others. 2020 · 2020
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Simcse: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
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Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2021 · 2021
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Constitutional ai: Harmlessness from ai feedback
Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, and 1 others. 2022 · 2022
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Promptagator: Few-shot dense retrieval from 8 examples
Zhuyun Dai, Vincent Y Zhao, Ji Ma, Yi Luan, Jianmo Ni, Jing Lu, Anton Bakalov, Kelvin Guu, Keith B Hall, and Ming-Wei Chang. 2022 · 2022
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Re2g: Retrieve, rerank, generate
Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, Ankita Rajaram Naik, Pengshan Cai, and Alfio Gliozzo. 2022 · 2022
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Recitation-augmented language models
Zhiqing Sun, Xuezhi Wang, Yi Tay, Yiming Yang, and Denny Zhou. 2022 · 2022
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Generate rather than retrieve: Large language models are strong context generators
Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, and Meng Jiang. 2022 · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, and 1 others. 2023 · 2023
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Detecting language model attacks with perplexity
Gabriel Alon and Michael Kamfonas. 2023 · 2023
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Walking down the memory maze: Beyond context limit through interactive reading
Howard Chen, Ramakanth Pasunuru, Jason Weston, and Asli Celikyilmaz. 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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Ambigdocs: Reasoning across documents on different entities under the same name
Yoonsang Lee, Xi Ye, and Eunsol Choi. 2024 · 2024
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Bing chat
Microsoft. 2024 · 2024
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Mistral-nemo-instruct-2407
Mistral-Nemo. 2024 · 2024
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Perplexity ai
AI Perplexity. 2024 · 2024
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A retrieval corruption attack
rocky. 2024 · 2024
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Machine against the rag: Jamming retrieval-augmented generation with blocker documents
Avital Shafran, Roei Schuster, and Vitaly Shmatikov. 2024 · 2024
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Not what you’ve signed up for: Compromising real-world llm-integrated applications with indirect prompt injection
Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, Christoph Endres, Thorsten Holz, and Mario Fritz. 2023 · 2023
Cited alongside, same era.
Atlas: Few-shot learning with retrieval augmented language models
Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, and Edouard Grave. 2023 · 2023
Cited alongside, same era.
Baseline defenses for adversarial attacks against aligned language models
Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping-yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, and Tom Goldstein. 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, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, and 1 others. 2023 · 2023
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Take a step back: Evoking reasoning via abstraction in large language models
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H Chi, Quoc V Le, and Denny Zhou. 2023 · 2023
Cited alongside, same era.
Poisoning retrieval corpora by injecting adversarial passages
Zexuan Zhong, Ziqing Huang, Alexander Wettig, and Danqi Chen. 2023 · 2023
Cited alongside, same era.
Glue pizza and eat rocks: Google ai search errors go viral
BBC. 2024 · 2024
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Generative ai in search: Let google do the searching for you
Google. 2024 · 2024
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" glue pizza and eat rocks"–exploiting vulnerabilities in retrieval-augmented generative models
Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Song Wang, Jundong Li, Tianlong Chen, and Huan Liu. 2024 · 2024
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Fei Wang, Xingchen Wan, Ruoxi Sun, Jiefeng Chen, and Sercan Ö Arık. 2024 · 2024
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Instructrag: Instructing retrieval-augmented generation with explicit denoising
Zhepei Wei, Wei-Lin Chen, and Yu Meng. 2024 · 2024
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Certifiably robust rag against retrieval corruption
Chong Xiang, Tong Wu, Zexuan Zhong, David Wagner, Danqi Chen, and Prateek Mittal. 2024 · 2024
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Trustworthiness in retrieval-augmented generation systems: A survey
Yujia Zhou, Yan Liu, Xiaoxi Li, Jiajie Jin, Hongjin Qian, Zheng Liu, Chaozhuo Li, Zhicheng Dou, Tsung-Yi Ho, and Philip S Yu. 2024 · 2024
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Poisonedrag: Knowledge corruption attacks to retrieval-augmented generation of large language models
Wei Zou, Runpeng Geng, Binghui Wang, and Jinyuan Jia. 2024 · 2024
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Retrieval-augmented generation with conflicting evidence
Han Wang, Archiki Prasad, Elias Stengel-Eskin, and Mohit Bansal. 2025 · 2025
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Adversarial decoding: Generating readable documents for adversarial objectives
Collin Zhang, Tingwei Zhang, and Vitaly Shmatikov. 2025 · 2025
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