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Retrieval-augmented generation (RAG) enhances large language models (LLMs) by integrating external knowledge retrieved from a knowledge base.
Statistical language models for information retrieval
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HotpotQA: A dataset for diverse, explainable multi-hop question answering
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Optimizing dense retrieval model training with hard negatives. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval . 1503–1512
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Improving language models by retrieving from trillions of tokens. In International conference on machine learning . PMLR, 2206–2240
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Murag: Multimodal retrieval-augmented generator for open question answering over images and text
Wenhu Chen, Hexiang Hu, Xi Chen, Pat Verga, and William W Cohen. 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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Synthetic disinformation attacks on automated fact verification systems. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 36. 10581–10589
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Re2G: Retrieve, rerank, generate
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Retrieval as attention: End-to-end learning of retrieval and reading within a single transformer
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A survey on retrieval-augmented text generation
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TegTok: Augmenting text generation via task-specific and open-world knowledge
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Performance of ChatGPT and GPT-4 on neurosurgery written board examinations
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Defending Against Misinformation Attacks in Open-Domain Question Answering
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Retrieving supporting evidence for generative question answering. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region . 11–20
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GRAG: Graph Retrieval-Augmented Generation
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Citation-Enhanced Generation for LLM-based Chatbot
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Graph retrieval-augmented generation: A survey
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Towards a search engine for machines: Unified ranking for multiple retrieval-augmented large language models. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval . 741–751
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Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, and Edouard Grave. 2023 · 2023
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Query rewriting for retrieval-augmented large language models
Xinbei Ma, Yeyun Gong, Pengcheng He, Hai Zhao, and Nan Duan. 2023a · 2023
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CaseEncoder: A Knowledge-enhanced Pre-trained Model for Legal Case Encoding
Yixiao Ma, Yueyue Wu, Weihang Su, Qingyao Ai, and Yiqun Liu. 2023b · 2023
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GPTEval: A survey on assessments of ChatGPT and GPT-4
Rui Mao, Guanyi Chen, Xulang Zhang, Frank Guerin, and Erik Cambria. 2023 · 2023
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On the risk of misinformation pollution with large language models
Yikang Pan, Liangming Pan, Wenhu Chen, Preslav Nakov, Min-Yen Kan, and William Yang Wang. 2023 · 2023
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Wikiformer: Pre-training with Structured Information of Wikipedia for Ad-hoc Retrieval
Weihang Su, Qingyao Ai, Xiangsheng Li, Jia Chen, Yiqun Liu, Xiaolong Wu, and Shengluan Hou. 2023a · 2023
Cited alongside, same era.
Caseformer: Pre-training for Legal Case Retrieval
Weihang Su, Qingyao Ai, Yueyue Wu, Yixiao Ma, Haitao Li, and Yiqun Liu. 2023b · 2023
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Thuir2 at ntcir-16 session search (ss) task
Weihang Su, Xiangsheng Li, Yiqun Liu, Min Zhang, and Shaoping Ma. 2023c · 2023
Cited alongside, same era.
Rulin Shao, Jacqueline He, Akari Asai, Weijia Shi, Tim Dettmers, Sewon Min, Luke Zettlemoyer, and Pang Wei Koh. 2024 · 2024
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STARD: A Chinese Statute Retrieval Dataset Derived from Real-life Queries by Non-professionals. In Findings of the Association for Computational Linguistics: EMNLP 2024 , Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen (Eds.). Association for Computational Linguistics, Miami, Florida, USA, 10658–10671
Weihang Su, Yiran Hu, Anzhe Xie, Qingyao Ai, Quezi Bing, Ning Zheng, Yun Liu, Weixing Shen, and Yiqun Liu. 2024a · 2024
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Mitigating entity-level hallucination in large language models. In Proceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region . 23–31
Weihang Su, Yichen Tang, Qingyao Ai, Changyue Wang, Zhijing Wu, and Yiqun Liu. 2024b · 2024
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Weihang Su, Yichen Tang, Qingyao Ai, Zhijing Wu, and Yiqun Liu. 2024c · 2024
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Unsupervised real-time hallucination detection based on the internal states of large language models
Weihang Su, Changyue Wang, Qingyao Ai, Yiran Hu, Zhijing Wu, Yujia Zhou, and Yiqun Liu. 2024d · 2024
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Knowledge Editing through Chain-of-Thought
Changyue Wang, Weihang Su, Qingyao Ai, and Yiqun Liu. 2024a · 2024
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LeKUBE: A Legal Knowledge Update BEnchmark
Changyue Wang, Weihang Su, Hu Yiran, Qingyao Ai, Yueyue Wu, Cheng Luo, Yiqun Liu, Min Zhang, and Shaoping Ma. 2024b · 2024
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Fei Wang, Xingchen Wan, Ruoxi Sun, Jiefeng Chen, and Sercan Ö Arık. 2024c · 2024
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InstructRAG: Instructing Retrieval Augmented Generation via Self-Synthesized Rationales
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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Corrective retrieval augmented generation
Shi-Qi Yan, Jia-Chen Gu, Yun Zhu, and Zhen-Hua Ling. 2024 · 2024
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An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al · 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 poisoning attacks to retrieval-augmented generation of large language models
Wei Zou, Runpeng Geng, Binghui Wang, and Jinyuan Jia. 2024 · 2024
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Decoupling Knowledge and Context: An Efficient and Effective Retrieval Augmented Generation Framework via Cross Attention. In Proceedings of the ACM on Web Conference 2025
Qian Dong, Qingyao Ai, Hongning Wang, Yiding Liu, Haitao Li, Weihang Su, Yiqun Liu, Tat-Seng Chua, and Shaoping Ma. 2025 · 2025
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Parametric Retrieval Augmented Generation
Weihang Su, Yichen Tang, Qingyao Ai, Junxi Yan, Changyue Wang, Hongning Wang, Ziyi Ye, Yujia Zhou, and Yiqun Liu. 2025 · 2025
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