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Text ranking is a critical task in information retrieval.
Multi-stage document ranking with BERT
Rodrigo Frassetto Nogueira, Wei Yang, Kyunghyun Cho, and Jimmy Lin. 2019 · 1910
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Pranking with ranking
Koby Crammer and Yoram Singer. 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
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Learning to rank using gradient descent
Chris Burges, Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton, and Greg Hullender. 2005 · 2005
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Subset ranking using regression
David Cossock and Tong Zhang. 2006 · 2006
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Listwise approach to learning to rank: theory and algorithm
Fen Xia, Tie-Yan Liu, Jue Wang, Wensheng Zhang, and Hang Li. 2008 · 2008
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Learning to rank for information retrieval
Tie-Yan Liu et al. 2009 · 2009
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The probabilistic relevance framework: BM25 and beyond
Stephen E. Robertson and Hugo Zaragoza. 2009 · 2009
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Yahoo! learning to rank challenge overview
Olivier Chapelle and Yi Chang. 2011 · 2010
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A deep relevance matching model for ad-hoc retrieval
Jiafeng Guo, Yixing Fan, Qingyao Ai, and W. Bruce Croft. 2016 · 2016
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MS MARCO: A human generated machine reading comprehension dataset
Tri Nguyen, Mir Rosenberg, et al. 2016 · 2016
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Text matching as image recognition
Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, Shengxian Wan, and Xueqi Cheng. 2016 · 2016
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al. 2018 · 2018
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton. 2020 · 2020
Cited alongside, same era.
Overview of the TREC 2020 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2021 · 2020
Cited alongside, same era.
Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasovic, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A. Smith. 2020 · 2020
Cited alongside, same era.
Document ranking with a pretrained sequence-to-sequence model
Rodrigo Frassetto Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin. 2020 · 2020
Cited alongside, same era.
Rethink training of BERT rerankers in multi-stage retrieval pipeline
Luyu Gao, Zhuyun Dai, and Jamie Callan. 2021 · 2021
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Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao et al. 2022 · 2022
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Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, Binyuan Hui, Luo Ji, Mei Li, Junyang Lin, Runji Lin, Dayiheng Liu, Gao Liu, Chengqiang Lu, Keming Lu, Jianxin Ma, Rui Men, Xingzhang Ren, Xuancheng Ren, Chuanqi Tan, Sinan Tan, Jianhong Tu, Peng Wang, Shijie Wang, Wei Wang, Shengguang Wu, Benfeng Xu, Jin Xu, An Yang, Hao Yang, Jian Yang, Shusheng Yang, Yang Yao, Bowen Yu, Hongyi Yuan, Zheng Yuan, Jianwei Zhang, Xingxuan Zhang, Yichang Zhang, Zhenru Zhang, Chang Zhou, Jingren Zhou, Xiaohuan Zhou, and Tianhang Zhu. 2023 · 2023
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Discrete prompt optimization via constrained generation for zero-shot re-ranker
Sukmin Cho, Soyeong Jeong, Jeongyeon Seo, and Jong C. Park. 2023 · 2023
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Parade: Passage ranking using demonstrations with large language models
Andrew Drozdov, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler, et al. 2023 · 2023
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Text-to-text multi-view learning for passage re-ranking
Jia-Huei Ju, Jheng-Hong Yang, and Chuan-Ju Wang. 2021 · 2021
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The expando-mono-duo design pattern for text ranking with pretrained sequence-to-sequence models
Ronak Pradeep, Rodrigo Frassetto Nogueira, and Jimmy Lin. 2021 · 2021
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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
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Holistic evaluation of language models
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, and Yuta Koreeda. 2022 · 2022
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SGPT: GPT sentence embeddings for semantic search
Niklas Muennighoff. 2022 · 2022
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Introducing chatgpt
OpenAI. 2022 · 2022
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Improving passage retrieval with zero-shot question generation
Devendra Singh Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, and Luke Zettlemoyer. 2022 · 2022
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Faa: Fine-grained attention alignment for cascade document ranking
Zhen Li, Chongyang Tao, Jiazhan Feng, Tao Shen, Dongyan Zhao, Xiubo Geng, and Daxin Jiang. 2023 · 2023
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OpenAI. 2023 · 2023
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Large language models are effective text rankers with pairwise ranking prompting
Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu, Jiaming Shen, Tianqi Liu, Jialu Liu, Donald Metzler, Xuanhui Wang, et al. 2023 · 2023
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Ul2: Unifying language learning paradigms
Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Xavier Garcia, Jason Wei, Xuezhi Wang, Hyung Won Chung, Siamak Shakeri, Dara Bahri, Tal Schuster, Huaixiu Steven Zheng, Denny Zhou, Neil Houlsby, and Donald Metzler. 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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Rankt5: Fine-tuning T5 for text ranking with ranking losses
Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, and Michael Bendersky. 2023b · 2023
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