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Using large language models (LMs) for query or document expansion can improve generalization in information retrieval.
Document expansion by query prediction
Rodrigo Nogueira, Wei Yang, Jimmy Lin, and Kyunghyun Cho. 2019c · 1904
Earlier work this paper cites.
Multi-stage document ranking with bert
Rodrigo Nogueira, Wei Yang, Kyunghyun Cho, and Jimmy Lin. 2019b · 1910
Earlier work this paper cites.
Www’18 open challenge: Financial opinion mining and question answering
Macedo Maia, Siegfried Handschuh, André Freitas, Brian Davis, Ross McDermott, Manel Zarrouk, and Alexandra Balahur. 2018 · 1942
Earlier work this paper cites.
Relevance feedback in information retrieval
Joseph John Rocchio Jr. 1971 · 1971
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Trec-4 experiments at dublin city university: Thresholding posting lists, query expansion with wordnet and pos tagging of spanish
Alan F Smeaton, Fergus Kelledy, and Ruairi O’Donnell. 1995 · 1995
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Relevance based language models
Victor Lavrenko and W. Bruce Croft. 2001 · 2001
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Overview of the trec 2019 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M Voorhees. 2020 · 2003
Earlier work this paper cites.
Towards collaborative information retrieval: Three approaches
Armin Hust, Stefan Klink, Markus Junker, and Andreas Dengel. 2003 · 2003
Earlier work this paper cites.
Umass at trec 2004: Novelty and hard
Nasreen Abdul-Jaleel, James Allan, W Bruce Croft, Fernando Diaz, Leah Larkey, Xiaoyan Li, Mark D Smucker, and Courtney Wade. 2004 · 2004
Earlier work this paper cites.
An effective approach to document retrieval via utilizing wordnet and recognizing phrases
Shuang Liu, Fang Liu, Clement T. Yu, and Weiyi Meng. 2004 · 2004
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A review of ontology based query expansion
Jagdev Bhogal, Andrew MacFarlane, and Peter Smith. 2007 · 2007
Earlier work this paper cites.
Bert-qe: contextualized query expansion for document re-ranking
Zhi Zheng, Kai Hui, Ben He, Xianpei Han, Le Sun, and Andrew Yates. 2020 · 2009
Earlier work this paper cites.
A survey of automatic query expansion in information retrieval
Claudio Carpineto and Giovanni Romano. 2012 · 2012
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A full-text learning to rank dataset for medical information retrieval
Vera Boteva, Demian Gholipour, Artem Sokolov, and Stefan Riezler. 2016 · 2016
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Ms marco: A human generated machine reading comprehension dataset
Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng. 2016 · 2016
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Quora question pairs
Shankar Iyer, Nikhil Dandekar, and Kornél Csernai. 2017 · 2017
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Retrieval of the best counterargument without prior topic knowledge
Henning Wachsmuth, Shahbaz Syed, and Benno Stein. 2018 · 2018
Earlier work this paper cites.
WikiQA: A challenge dataset for open-domain question answering
Yi Yang, Wen-tau Yih, and Christopher Meek. 2015 · 2018
Earlier work this paper cites.
Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Earlier work this paper cites.
Overview of Touché 2020: Argument Retrieval
Alexander Bondarenko, Maik Fröbe, Meriem Beloucif, Lukas Gienapp, Yamen Ajjour, Alexander Panchenko, Chris Biemann, Benno Stein, Henning Wachsmuth, Martin Potthast, and Matthias Hagen. 2020 · 2020
Earlier work this paper cites.
Overview of the trec 2020 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2021 · 2020
Cited alongside, same era.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen Tau Yih. 2020 · 2020
Cited alongside, same era.
Document ranking with a pretrained sequence-to-sequence model
Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin. 2020 · 2020
Cited alongside, same era.
Fact or fiction: Verifying scientific claims
David Wadden, Shanchuan Lin, Kyle Lo, Lucy Lu Wang, Madeleine van Zuylen, Arman Cohan, and Hannaneh Hajishirzi. 2020 · 2020
Cited alongside, same era.
Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers
Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, and Ming Zhou. 2020 · 2020
Cited alongside, same era.
GPL: Generative pseudo labeling for unsupervised domain adaptation of dense retrieval
Kexin Wang, Nandan Thakur, Nils Reimers, and Iryna Gurevych. 2022a · 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 · 2022
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Defending against misinformation attacks in open-domain question answering
Orion Weller, Aleem Khan, Nathaniel Weir, Dawn Lawrie, and Benjamin Van Durme. 2022 · 2022
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On the effects of regional spelling conventions in retrieval models
Andreas Chari, Sean MacAvaney, and Iadh Ounis. 2023 · 2023
Closest in time.
Perspectives on large language models for relevance judgment
Guglielmo Faggioli, Laura Dietz, Charles L. A. Clarke, Gianluca Demartini, Matthias Hagen, Claudia Hauff, Noriko Kando, Evangelos Kanoulas, Martin Potthast, Benno Stein, and Henning Wachsmuth. 2023 · 2023
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Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2021 · 2021
Cited alongside, same era.
GooAQ: Open question answering with diverse answer types
Daniel Khashabi, Amos Ng, Tushar Khot, Ashish Sabharwal, Hannaneh Hajishirzi, and Chris Callison-Burch. 2021 · 2021
Cited alongside, same era.
Overview of the trec 2021 clinical trials track
Kirk Roberts, Dina Demner-Fushman, Ellen M Voorhees, Steven Bedrick, and Willian R Hersh. 2021 · 2021
Cited alongside, same era.
BEIR: A heterogeneous benchmark for zero-shot evaluation of information retrieval models
Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych. 2021 · 2021
Cited alongside, same era.
Pretrained transformers for text ranking: BERT and beyond
Andrew Yates, Rodrigo Nogueira, and Jimmy Lin. 2021 · 2021
Cited alongside, same era.
Task-aware retrieval with instructions
Akari Asai, Timo Schick, Patrick Lewis, Xilun Chen, Gautier Izacard, Sebastian Riedel, Hannaneh Hajishirzi, and Wen-tau Yih. 2022 · 2022
Cited alongside, same era.
Salient phrase aware dense retrieval: Can a dense retriever imitate a sparse one?
Xilun Chen, Kushal Lakhotia, Barlas Oguz, Anchit Gupta, Patrick Lewis, Stan Peshterliev, Yashar Mehdad, Sonal Gupta, and Wen-tau Yih. 2022 · 2022
Cited alongside, same era.
Robustqa: Benchmarking the robustness of domain adaptation for open-domain question answering
Rujun Han, Peng Qi, Yuhao Zhang, Lan Liu, Juliette Burger, William Yang Wang, Zhiheng Huang, Bing Xiang, and Dan Roth. 2023 · 2023
Closest in time.
Query expansion by prompting large language models
Rolf Jagerman, Honglei Zhuang, Zhen Qin, Xuanhui Wang, and Michael Bendersky. 2023 · 2023
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Inpars-v2: Large language models as efficient dataset generators for information retrieval
Vitor Jeronymo, Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, Roberto Lotufo, Jakub Zavrel, and Rodrigo Nogueira. 2023 · 2023
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Towards general text embeddings with multi-stage contrastive learning
Zehan Li, Xin Zhang, Yanzhao Zhang, Dingkun Long, Pengjun Xie, and Meishan Zhang. 2023 · 2023
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Decomposing complex queries for tip-of-the-tongue retrieval
Kevin Lin, Kyle Lo, Joseph E Gonzalez, and Dan Klein. 2023 · 2023
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Ms-shift: An analysis of ms marco distribution shifts on neural retrieval
Simon Lupart, Thibault Formal, and Stéphane Clinchant. 2023 · 2023
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One-shot labeling for automatic relevance estimation
Sean MacAvaney and Luca Soldaini. 2023 · 2023
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Generative relevance feedback with large language models
Iain Mackie, Shubham Chatterjee, and Jeffrey Stephen Dalton. 2023 · 2023
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Synthetic cross-language information retrieval training data
James Mayfield, Eugene Yang, Dawn Lawrie, Samuel Barham, Orion Weller, Marc Mason, Suraj Nair, and Scott Miller. 2023 · 2023
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Retrieving texts based on abstract descriptions
Shauli Ravfogel, Valentina Pyatkin, Amir D. N. Cohen, Avshalom Manevich, and Yoav Goldberg. 2023 · 2023
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Large language models can accurately predict searcher preferences
Paul Thomas, Seth Spielman, Nick Craswell, and Bhaskar Mitra. 2023 · 2023
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Nevir: Negation in neural information retrieval
Orion Weller, Dawn J Lawrie, and Benjamin Van Durme. 2023 · 2023
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Large language models for information retrieval: A survey
Yutao Zhu, Huaying Yuan, Shuting Wang, Jiongnan Liu, Wenhan Liu, Chenlong Deng, Zhicheng Dou, and Ji rong Wen. 2023 · 2023
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MTEB: Massive text embedding benchmark
Niklas Muennighoff, Nouamane Tazi, Loic Magne, and Nils Reimers. 2023 · 2037
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