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Information retrieval (IR) systems have played a vital role in modern digital life and have cemented their continued usefulness in this new era of generative AI via retrieval-augmented generation.
The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson and Hugo Zaragoza · 2009
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyung Hyun Cho, and Yoshua Bengio · 2015
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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
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Dbpedia-entity v2: a test collection for entity search
Faegheh Hasibi, Fedor Nikolaev, Chenyan Xiong, Krisztian Balog, Svein Erik Bratsberg, Alexander Kotov, and Jamie Callan · 2017
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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
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Fever: a large-scale dataset for fact extraction and verification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal · 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
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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, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov · 2019
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Multi-stage document ranking with bert
Rodrigo Nogueira, Wei Yang, Kyunghyun Cho, and Jimmy Lin · 2019
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Is attention interpretable?
Sofia Serrano and Noah A. Smith · 2019
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Attention is not not explanation
Sarah Wiegreffe and Yuval Pinter · 2019
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Specter: Document-level representation learning using citation-informed transformers
Arman Cohan, Sergey Feldman, Iz Beltagy, Doug Downey, and Daniel S Weld · 2020
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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
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Climate-fever: A dataset for verification of real-world climate claims
Thomas Diggelmann, Jordan Boyd-Graber, Jannis Bulian, Massimiliano Ciaramita, and Markus Leippold · 2020
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Constructing a multi-hop qa dataset for comprehensive evaluation of reasoning steps
Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, and Akiko Aizawa · 2020
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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
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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, et al · 2020
Cited alongside, same era.
Document ranking with a pretrained sequence-to-sequence model
Rodrigo Nogueira, Zhiying Jiang, and Jimmy Lin · 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
Cited alongside, same era.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush · 2020
Cited alongside, same era.
Distilling knowledge from reader to retriever for question answering
Gautier Izacard and Edouard Grave · 2021
Zero-shot listwise document reranking with a large language model, 2023
Xueguang Ma, Xinyu Zhang, Ronak Pradeep, and Jimmy Lin · 2023
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Attention sorting combats recency bias in long context language models
Alexander Peysakhovich and Adam Lerer · 2023
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Is ChatGPT good at search? investigating large language models as re-ranking agents
Weiwei Sun, Lingyong Yan, Xinyu Ma, Shuaiqiang Wang, Pengjie Ren, Zhumin Chen, Dawei Yin, and Zhaochun Ren · 2023
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Found in the middle: Permutation self-consistency improves listwise ranking in large language models
Raphael Tang, Xinyu Zhang, Xueguang Ma, Jimmy Lin, and Ferhan Ture · 2023
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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
Cited alongside, same era.
Trec-covid: constructing a pandemic information retrieval test collection
Ellen Voorhees, Tasmeer Alam, Steven Bedrick, Dina Demner-Fushman, William R Hersh, Kyle Lo, Kirk Roberts, Ian Soboroff, and Lucy Lu Wang · 2021
Cited alongside, same era.
Calibrate before use: Improving few-shot performance of language models
Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh · 2021
Cited alongside, same era.
Improving passage retrieval with zero-shot question generation
Devendra Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, and Luke Zettlemoyer · 2022
Cited alongside, same era.
ColBERTv2: Effective and efficient retrieval via lightweight late interaction
Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, Christopher Potts, and Matei Zaharia · 2022
Cited alongside, same era.
Musique: Multihop questions via single-hop question composition
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal · 2022
Cited alongside, same era.
PaRaDe: Passage ranking using demonstrations with LLMs
Andrew Drozdov, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler, and Kai Hui · 2023
Cited alongside, same era.
Yutao Zhu, Huaying Yuan, Shuting Wang, Jiongnan Liu, Wenhan Liu, Chenlong Deng, Haonan Chen, Zhicheng Dou, and Ji-Rong Wen · 2023
Later among the works it cites.
Yiqun Chen, Qi Liu, Yi Zhang, Weiwei Sun, Daiting Shi, Jiaxin Mao, and Dawei Yin · 2024
Closest in time.
The llama 3 herd of models, 2024
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
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Bias and fairness in large language models: A survey
Isabel O Gallegos, Ryan A Rossi, Joe Barrow, Md Mehrab Tanjim, Sungchul Kim, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, and Nesreen K Ahmed · 2024
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Hipporag: Neurobiologically inspired long-term memory for large language models, 2024
Bernal Jiménez Gutiérrez, Yiheng Shu, Yu Gu, Michihiro Yasunaga, and Yu Su · 2024
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Lost in the middle: How language models use long contexts
Nelson F Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang · 2024
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Hello gpt-4o
OpenAI · 2024
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Large language models are effective text rankers with pairwise ranking prompting, 2024
Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu, Le Yan, Jiaming Shen, Tianqi Liu, Jialu Liu, Donald Metzler, Xuanhui Wang, and Michael Bendersky · 2024
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First: Faster improved listwise reranking with single token decoding, 2024
Revanth Gangi Reddy, JaeHyeok Doo, Yifei Xu, Md Arafat Sultan, Deevya Swain, Avirup Sil, and Heng Ji · 2024
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Large search model: Redefining search stack in the era of llms
Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, and Furu Wei · 2024
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A setwise approach for effective and highly efficient zero-shot ranking with large language models
Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, and Guido Zuccon · 2024
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