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Recently, generative retrieval emerges as a promising alternative to traditional retrieval paradigms.
Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrieval
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Natural Questions: a Benchmark for Question Answering Research
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Efficient Graph Generation with Graph Recurrent Attention Networks. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada , Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d’Alché-Buc, Emily B. Fox, and Roman Garnett (Eds.). 4257–4267
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Deep Set Prediction Networks. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada , Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d’Alché-Buc, Emily B. Fox, and Roman Garnett (Eds.). 3207–3217
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GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation. In WWW ’20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020 , Yennun Huang, Irwin King, Tie-Yan Liu, and Maarten van Steen (Eds.). ACM / IW3C2, 1253–1263
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Dense Passage Retrieval for Open-Domain Question Answering. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16-20, 2020 , Bonnie Webber, Trevor Cohn, Yulan He, and Yang Liu (Eds.). Association for Computational Linguistics, 6769–6781
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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Autoregressive Entity Retrieval. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021 . OpenReview.net
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SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval
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SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking. In SIGIR ’21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021 , Fernando Diaz, Chirag Shah, Torsten Suel, Pablo Castells, Rosie Jones, and Tetsuya Sakai (Eds.). ACM, 2288–2292
Thibault Formal, Benjamin Piwowarski, and Stéphane Clinchant. 2021b · 2021
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Jimmy Lin and Xueguang Ma. 2021 · 2021
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Learning Passage Impacts for Inverted Indexes. In SIGIR ’21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021 , Fernando Diaz, Chirag Shah, Torsten Suel, Pablo Castells, Rosie Jones, and Tetsuya Sakai (Eds.). ACM, 1723–1727
Antonio Mallia, Omar Khattab, Torsten Suel, and Nicola Tonellotto. 2021 · 2021
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Rethinking search: making domain experts out of dilettantes
Donald Metzler, Yi Tay, Dara Bahri, and Marc Najork. 2021 · 2021
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RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2021, Online, June 6-11, 2021 , Kristina Toutanova, Anna Rumshisky, Luke Zettlemoyer, Dilek Hakkani-Tür, Iz Beltagy, Steven Bethard, Ryan Cotterell, Tanmoy Chakraborty, and Yichao Zhou (Eds.). Association for Computational Linguistics, 5835–5847
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Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021 . OpenReview.net
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul N. Bennett, Junaid Ahmed, and Arnold Overwijk. 2021 · 2021
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Optimizing Dense Retrieval Model Training with Hard Negatives. In SIGIR ’21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021 , Fernando Diaz, Chirag Shah, Torsten Suel, Pablo Castells, Rosie Jones, and Tetsuya Sakai (Eds.). ACM, 1503–1512
Continual Learning for Generative Retrieval over Dynamic Corpora
Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Yixing Fan, and Xueqi Cheng. 2023b · 2023
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A Unified Generative Retriever for Knowledge-Intensive Language Tasks via Prompt Learning. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, July 23-27, 2023 , Hsin-Hsi Chen, Wei-Jou (Edward) Duh, Hen-Hsen Huang, Makoto P. Kato, Josiane Mothe, and Barbara Poblete (Eds.). ACM, 1448–1457
Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Yiqun Liu, Yixing Fan, and Xueqi Cheng. 2023c · 2023
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Fitting Autoregressive Graph Generative Models through Maximum Likelihood Estimation
Xu Han, Xiaohui Chen, Francisco J. R. Ruiz, and Li-Ping Liu. 2023 · 2023
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Learning to rank in generative retrieval
Yongqi Li, Nan Yang, Liang Wang, Furu Wei, and Wenjie Li. 2023a · 2023
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Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, and Shaoping Ma. 2021 · 2021
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Autoregressive Search Engines: Generating Substrings as Document Identifiers. In Advances in Neural Information Processing Systems , Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho (Eds.)
Michele Bevilacqua, Giuseppe Ottaviano, Patrick Lewis, Scott Yih, Sebastian Riedel, and Fabio Petroni. 2022 · 2022
Cited alongside, same era.
CorpusBrain: Pre-Train a Generative Retrieval Model for Knowledge-Intensive Language Tasks (CIKM ’22) . Association for Computing Machinery, New York, NY, USA, 191–200
Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Yiqun Liu, Yixing Fan, and Xueqi Cheng. 2022 · 2022
Cited alongside, same era.
Multilingual Autoregressive Entity Linking
Nicola De Cao, Ledell Wu, Kashyap Popat, Mikel Artetxe, Naman Goyal, Mikhail Plekhanov, Luke Zettlemoyer, Nicola Cancedda, Sebastian Riedel, and Fabio Petroni. 2022 · 2022
Cited alongside, same era.
Stochastic Optimization of Text Set Generation for Learning Multiple Query Intent Representations. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022 , Mohammad Al Hasan and Li Xiong (Eds.). ACM, 4003–4008
Helia Hashemi, Hamed Zamani, and W. Bruce Croft. 2022 · 2022
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Yuxiang Lu, Yiding Liu, Jiaxiang Liu, Yunsheng Shi, Zhengjie Huang, Shikun Feng, Yu Sun, Hao Tian, Hua Wu, Shuaiqiang Wang, Dawei Yin, and Haifeng Wang. 2022 · 2022
Cited alongside, same era.
DSI++: Updating Transformer Memory with New Documents
Sanket Vaibhav Mehta, Jai Prakash Gupta, Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Jinfeng Rao, Marc Najork, Emma Strubell, and Donald Metzler. 2022 · 2022
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WebGPT: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, Tyna Eloundou, Gretchen Krueger, Kevin Button, Matthew Knight, Benjamin Chess, and John Schulman. 2022 · 2022
Cited alongside, same era.
Large Dual Encoders Are Generalizable Retrievers. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7-11, 2022 , Yoav Goldberg, Zornitsa Kozareva, and Yue Zhang (Eds.). Association for Computational Linguistics, 9844–9855
Jianmo Ni, Chen Qu, Jing Lu, Zhuyun Dai, Gustavo Hernández Abrego, Ji Ma, Vincent Y. Zhao, Yi Luan, Keith B. Hall, Ming-Wei Chang, and Yinfei Yang. 2022 · 2022
Cited alongside, same era.
Transformer Memory as a Differentiable Search Index
Yi Tay, Vinh Q. Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Prakash Gupta, Tal Schuster, William W. Cohen, and Donald Metzler. 2022 · 2022
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Multiview Identifiers Enhanced Generative Retrieval. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2023, Toronto, Canada, July 9-14, 2023 , Anna Rogers, Jordan L. Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, 6636–6648
Yongqi Li, Nan Yang, Liang Wang, Furu Wei, and Wenjie Li. 2023b · 2023
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How Does Generative Retrieval Scale to Millions of Passages?
Ronak Pradeep, Kai Hui, Jai Gupta, Adam D. Lelkes, Honglei Zhuang, Jimmy Lin, Donald Metzler, and Vinh Q. Tran. 2023 · 2023
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Recommender Systems with Generative Retrieval
Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan H. Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, and Maheswaran Sathiamoorthy. 2023 · 2023
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Learning to Tokenize for Generative Retrieval
Weiwei Sun, Lingyong Yan, Zheng Chen, Shuaiqiang Wang, Haichao Zhu, Pengjie Ren, Zhumin Chen, Dawei Yin, Maarten de Rijke, and Zhaochun Ren. 2023 · 2023
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Semantic-Enhanced Differentiable Search Index Inspired by Learning Strategies. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023 , Ambuj K. Singh, Yizhou Sun, Leman Akoglu, Dimitrios Gunopulos, Xifeng Yan, Ravi Kumar, Fatma Ozcan, and Jieping Ye (Eds.). ACM, 4904–4913
Yubao Tang, Ruqing Zhang, Jiafeng Guo, Jiangui Chen, Zuowei Zhu, Shuaiqiang Wang, Dawei Yin, and Xueqi Cheng. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study
Boxin Wang, Wei Ping, Peng Xu, Lawrence McAfee, Zihan Liu, Mohammad Shoeybi, Yi Dong, Oleksii Kuchaiev, Bo Li, Chaowei Xiao, Anima Anandkumar, and Bryan Catanzaro. 2023 · 2023
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C-Pack: Packaged Resources To Advance General Chinese Embedding
Shitao Xiao, Zheng Liu, Peitian Zhang, and Niklas Muennighoff. 2023 · 2023
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Auto Search Indexer for End-to-End Document Retrieval. In Findings of the Association for Computational Linguistics: EMNLP 2023, Singapore, December 6-10, 2023 , Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, 6955–6970
Tianchi Yang, Minghui Song, Zihan Zhang, Haizhen Huang, Weiwei Deng, Feng Sun, and Qi Zhang. 2023 · 2023
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Scalable and Effective Generative Information Retrieval
Hansi Zeng, Chen Luo, Bowen Jin, Sheikh Muhammad Sarwar, Tianxin Wei, and Hamed Zamani. 2023 · 2023
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Hybrid Inverted Index Is a Robust Accelerator for Dense Retrieval. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, December 6-10, 2023 , Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, 1877–1888
Peitian Zhang, Zheng Liu, Shitao Xiao, Zhicheng Dou, and Jing Yao. 2023a · 2023
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Retrieve Anything To Augment Large Language Models
Peitian Zhang, Shitao Xiao, Zheng Liu, Zhicheng Dou, and Jian-Yun Nie. 2023b · 2023
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Enhancing Generative Retrieval with Reinforcement Learning from Relevance Feedback. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, December 6-10, 2023 , Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, 12481–12490
Yujia Zhou, Zhicheng Dou, and Ji-Rong Wen. 2023a · 2023
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DynamicRetriever: A Pre-trained Model-based IR System Without an Explicit Index
Yujia Zhou, Jing Yao, Zhicheng Dou, Ledell Wu, and Ji-Rong Wen. 2023b · 2023
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UniGen: A Unified Generative Framework for Retrieval and Question Answering with Large Language Models. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 8688–8696
Xiaoxi Li, Yujia Zhou, and Zhicheng Dou. 2024 · 2024
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