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This paper introduces PAG-a novel optimization and decoding approach that guides autoregressive generation of document identifiers in generative retrieval models through simultaneous decoding.
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Autoregressive Search Engines: Generating Substrings as Document Identifiers
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Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors
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From Neural Re-Ranking to Neural Ranking: Learning a Sparse Representation for Inverted Indexing
Hamed Zamani, Mostafa Dehghani, W. Bruce Croft, Erik G. Learned-Miller, and J. Kamps. 2018 · 2018
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In North American Chapter of the Association for Computational Linguistics
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Natural Questions: A Benchmark for Question Answering Research
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DSI++: Updating Transformer Memory with New Documents
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Training language models to follow instructions with human feedback
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Transformer Memory as a Differentiable Search Index
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A Neural Corpus Indexer for Document Retrieval
Yujing Wang, Ying Hou, Hong Wang, Ziming Miao, Shibin Wu, Hao Sun, Qi Chen, Yuqing Xia, Chengmin Chi, Guoshuai Zhao, Zheng Liu, Xing Xie, Hao Sun, Weiwei Deng, Qi Zhang, and Mao Yang. 2022 · 2022
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Retrieval-Enhanced Machine Learning. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (Madrid, Spain) (SIGIR ’22) . Association for Computing Machinery, New York, NY, USA, 2875–2886
Hamed Zamani, Fernando Diaz, Mostafa Dehghani, Donald Metzler, and Michael Bendersky. 2022 · 2022
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Curriculum Learning for Dense Retrieval Distillation
Hansi Zeng, Hamed Zamani, and Vishwa Vinay. 2022 · 2022
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Ultron: An Ultimate Retriever on Corpus with a Model-based Indexer
Yujia Zhou, Jing Yao, Zhicheng Dou, Ledell Yu Wu, Peitian Zhang, and Ji rong Wen. 2022 · 2022
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FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (Taipei, Taiwan) (SIGIR ’23) . Association for Computing Machinery, New York, NY, USA, 1437–1447
Sebastian Hofstätter, Jiecao Chen, Karthik Raman, and Hamed Zamani. 2023 · 2023
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How Does Generative Retrieval Scale to Millions of Passages?
Ronak Pradeep, Kai Hui, Jai Gupta, Ádám Dániel 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 Hieu 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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TOME: A Two-stage Approach for Model-based Retrieval
Ruiyang Ren, Wayne Xin Zhao, J. Liu, Huaqin Wu, Ji rong Wen, and Haifeng Wang. 2023 · 2023
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A Symmetric Dual Encoding Dense Retrieval Framework for Knowledge-Intensive Visual Question Answering. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (Taipei, Taiwan) (SIGIR ’23) . Association for Computing Machinery, New York, NY, USA, 110–120
Alireza Salemi, Juan Altmayer Pizzorno, and Hamed Zamani. 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, M. de Rijke, and Zhaochun Ren. 2023 · 2023
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NOVO: Learnable and Interpretable Document Identifiers for Model-Based IR
Zihan Wang, Yujia Zhou, Yiteng Tu, and Zhicheng Dou. 2023 · 2023
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LED: Lexicon-Enlightened Dense Retriever for Large-Scale Retrieval
Kai Zhang, Chongyang Tao, Tao Shen, Can Xu, Xiubo Geng, Binxing Jiao, and Daxin Jiang. 2022 · 2023
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Term-Sets Can Be Strong Document Identifiers For Auto-Regressive Search Engines
Peitian Zhang, Zheng Liu, Yujia Zhou, Zhicheng Dou, and Zhao Cao. 2023 · 2023
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Scalable and Effective Generative Information Retrieval. In Proceedings of the 2024 Web Conference (Singapore, Singapore) (WWW ’24)
Hansi Zeng, Chen Luo, Bowen Jin, Sheikh Muhammad Sarwar, Tianxin Wei, and Hamed Zamani. 2024 · 2024
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