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Large language models (LLMs) have shown nearly saturated performance on many natural language processing (NLP) tasks.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Leveraging passage retrieval with generative models for open domain question answering
Gautier Izacard and Edouard Grave. 2020 · 2007
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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, et al. 2019 · 2019
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Big bird: Transformers for longer sequences
Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, et al. 2020 · 2020
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A dataset for answering time-sensitive questions
Wenhu Chen, Xinyi Wang, and William Yang Wang. 2021 · 2021
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Gpt-j-6b: A 6 billion parameter autoregressive language model
Ben Wang and Aran Komatsuzaki. 2021 · 2021
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Situatedqa: Incorporating extra-linguistic contexts into qa
Michael JQ Zhang and Eunsol Choi. 2021 · 2021
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Are larger pretrained language models uniformly better? comparing performance at the instance level
Ruiqi Zhong, Dhruba Ghosh, Dan Klein, and Jacob Steinhardt. 2021 · 2021
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Gpt-neox-20b: An open-source autoregressive language model
Sid Black, Stella Biderman, Eric Hallahan, Quentin Anthony, Leo Gao, Laurence Golding, Horace He, Connor Leahy, Kyle McDonell, Jason Phang, et al. 2022 · 2022
Earlier work this paper cites.
Wenhu Chen, Xueguang Ma, Xinyi Wang, and William W Cohen. 2022 · 2022
Earlier work this paper cites.
Realtime qa: What’s the answer right now?
Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, Ronan Le Bras, Akari Asai, Xinyan Yu, Dragomir Radev, Noah A Smith, Yejin Choi, and Kentaro Inui. 2022 · 2022
Cited alongside, same era.
Fangyu Lei, Shizhu He, Xiang Li, Jun Zhao, and Kang Liu. 2022 · 2022
Cited alongside, same era.
Learning to imagine: Integrating counterfactual thinking in neural discrete reasoning
Moxin Li, Fuli Feng, Hanwang Zhang, Xiangnan He, Fengbin Zhu, and Tat-Seng Chua. 2022 · 2022
Cited alongside, same era.
Streamingqa: A benchmark for adaptation to new knowledge over time in question answering models
Adam Liska, Tomas Kocisky, Elena Gribovskaya, Tayfun Terzi, Eren Sezener, Devang Agrawal, D’Autume Cyprien De Masson, Tim Scholtes, Manzil Zaheer, Susannah Young, et al. 2022 · 2022
Cited alongside, same era.
Language models are greedy reasoners: A systematic formal analysis of chain-of-thought
Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al. 2022 · 2022
Later among the works it cites.
S3HQA: A three-stage approach for multi-hop text-table hybrid question answering
Fangyu Lei, Xiang Li, Yifan Wei, Shizhu He, Yiming Huang, Jun Zhao, and Kang Liu. 2023 · 2023
Closest in time.
Counterfactual reasoning: Testing language models’ understanding of hypothetical scenarios
Jiaxuan Li, Lang Yu, and Allyson Ettinger. 2023 · 2023
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OpenAI. 2023 · 2023
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Towards benchmarking and improving the temporal reasoning capability of large language models
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Abulhair Saparov and He He. 2022 · 2022
Cited alongside, same era.
Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, et al. 2022 · 2022
Cited alongside, same era.
Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al. 2022 · 2022
Cited alongside, same era.
React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022 · 2022
Cited alongside, same era.
Glm-130b: An open bilingual pre-trained model
Aohan Zeng, Xiao Liu, Zhengxiao Du, Zihan Wang, Hanyu Lai, Ming Ding, Zhuoyi Yang, Yifan Xu, Wendi Zheng, Xiao Xia, et al. 2022 · 2022
Cited alongside, same era.
Qingyu Tan, Hwee Tou Ng, and Lidong Bing. 2023 · 2023
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Learning to imagine: Visually-augmented natural language generation
Tianyi Tang, Yushuo Chen, Yifan Du, Junyi Li, Wayne Xin Zhao, and Ji-Rong Wen. 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, et al. 2023 · 2023
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Multi-view graph representation learning for answering hybrid numerical reasoning question
Yifan Wei, Fangyu Lei, Yuanzhe Zhang, Jun Zhao, and Kang Liu. 2023 · 2023
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Context-faithful prompting for large language models
Wenxuan Zhou, Sheng Zhang, Hoifung Poon, and Muhao Chen. 2023 · 2023
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