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Large Language Models (LLMs) have demonstrated remarkable zero-shot generalization across various language-related tasks, including search engines.
Rodrigo Nogueira and Kyunghyun Cho. 2019 · 1901
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Learning to rank using gradient descent
Christopher J. C. Burges, Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton, and Gregory N. Hullender. 2005 · 2005
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Ms marco: A human generated machine reading comprehension dataset
Daniel Fernando Campos, Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, Li Deng, and Bhaskar Mitra. 2016 · 2016
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The lambdaloss framework for ranking metric optimization
Xuanhui Wang, Cheng Li, Nadav Golbandi, Michael Bendersky, and Marc Najork. 2018 · 2018
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An analysis of the softmax cross entropy loss for learning-to-rank with binary relevance
Sebastian Bruch, Xuanhui Wang, Michael Bendersky, and Marc Najork. 2019 · 2019
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, T. J. Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
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Overview of the trec 2020 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Fernando Campos, and Ellen M. Voorhees. 2020 · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Yu Wu, Sergey Edunov, Danqi Chen, and Wen tau Yih. 2020 · 2020
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Pretrained transformers for text ranking: Bert and beyond
Jimmy J. Lin, Rodrigo Nogueira, and Andrew Yates. 2020 · 2020
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Document ranking with a pretrained sequence-to-sequence model
Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin. 2020 · 2020
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Shallow pooling for sparse labels
Negar Arabzadeh, Alexandra Vtyurina, Xinyi Yan, and Charles L. A. Clarke. 2021 · 2021
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mmarco: A multilingual version of ms marco passage ranking dataset
Luiz Henrique Bonifacio, Israel Campiotti, Roberto de Alencar Lotufo, and Rodrigo Nogueira. 2021 · 2021
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Autoregressive entity retrieval
Nicola De Cao, Gautier Izacard, Sebastian Riedel, and Fabio Petroni. 2021 · 2021
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Webgpt: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, S. Arun 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. 2021 · 2021
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Beir: A heterogenous benchmark for zero-shot evaluation of information retrieval models
Nandan Thakur, Nils Reimers, Andreas Ruckl’e, Abhishek Srivastava, and Iryna Gurevych. 2021 · 2021
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Mr. tydi: A multi-lingual benchmark for dense retrieval
Xinyu Zhang, Xueguang Ma, Peng Shi, and Jimmy J. Lin. 2021 · 2021
Cited alongside, same era.
Inpars: Data augmentation for information retrieval using large language models
Luiz Henrique Bonifacio, Hugo Queiroz Abonizio, Marzieh Fadaee, and Rodrigo Nogueira. 2022 · 2022
Cited alongside, same era.
Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, S. Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Dasha Valter, Sharan Narang, Gaurav Mishra, Adams Wei Yu, Vincent Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed Huai hsin Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, and Jason Wei. 2022 · 2022
Cited alongside, same era.
Pre-training methods in information retrieval
Yixing Fan, Xiaohui Xie, Yinqiong Cai, Jia Chen, Xinyu Ma, Xiangsheng Li, Ruqing Zhang, and Jiafeng Guo. 2022 · 2022
Cited alongside, same era.
Towards unsupervised dense information retrieval with contrastive learning
Precise zero-shot dense retrieval without relevance labels
Luyu Gao, Xueguang Ma, Jimmy Lin, and Jamie Callan. 2023 · 2023
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Few-shot learning with retrieval augmented language models
Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane A. Yu, Armand Joulin, Sebastian Riedel, and Edouard Grave. 2023 · 2023
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Zero-shot listwise document reranking with a large language model
Xueguang Ma, Xinyu Crystina Zhang, Ronak Pradeep, and Jimmy Lin. 2023 · 2023
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Teaching small language models to reason
Lucie Charlotte Magister, Jonathan Mallinson, Jakub Adamek, Eric Malmi, and Aliaksei Severyn. 2023 · 2023
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Confirmed: the new bing runs on openai’s gpt-4
Microsoft. 2023 · 2023
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Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2022 · 2022
Cited alongside, same era.
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 R’e, Diana Acosta-Navas, Drew A. Hudson, E. Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan S. Kim, Neel Guha, Niladri S. Chatterji, O. Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas F. Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, and Yuta Koreeda. 2022 · 2022
Cited alongside, same era.
Sgpt: Gpt sentence embeddings for semantic search
Niklas Muennighoff. 2022 · 2022
Cited alongside, same era.
Introducing chatgpt
OpenAI. 2022 · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke E. Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Francis Christiano, Jan Leike, and Ryan J. Lowe. 2022 · 2022
Cited alongside, same era.
Improving passage retrieval with zero-shot question generation
Devendra Singh Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen tau Yih, Joëlle Pineau, and Luke Zettlemoyer. 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 Gupta, Tal Schuster, William W. Cohen, and Donald Metzler. 2022 · 2022
Cited alongside, same era.
Pre-trained language model based ranking in baidu search
Lixin Zou, Shengqiang Zhang, Hengyi Cai, Dehong Ma, Suqi Cheng, Daiting Shi, Shuaiqiang Wang, Zhicong Cheng, and Dawei Yin. 2021 · 2022
Cited alongside, same era.
OpenAI. 2023 · 2023
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Questions are all you need to train a dense passage retriever
Devendra Singh Sachan, Mike Lewis, Dani Yogatama, Luke Zettlemoyer, Joëlle Pineau, and Manzil Zaheer. 2023 · 2023
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Replug: Retrieval-augmented black-box language models
Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, Mike Lewis, Luke Zettlemoyer, and Wen tau Yih. 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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Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 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, Aur’elien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
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Self-instruct: Aligning language model with self generated instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2023b · 2023
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Generate rather than retrieve: Large language models are strong context generators
Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, and Meng Jiang. 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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