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Large language models have recently been shown to attain reasonable zero-shot generalization on a diverse set of tasks (Brown et al., 2020).
Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
R. Thomas McCoy, Ellie Pavlick, and Tal Linzen · 1902
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DREAM: A challenge dataset and models for dialogue-based reading comprehension
Kai Sun, Dian Yu, Jianshu Chen, Dong Yu, Yejin Choi, and Claire Cardie · 1902
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Boolq: Exploring the surprising difficulty of natural yes/no questions
Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova · 1905
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Superglue: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman · 1905
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WINOGRANDE: an adversarial winograd schema challenge at scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi · 1907
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Release strategies and the social impacts of language models
Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, and Jasmine Wang · 1908
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Multitask learning
Rich Caruana · 1997
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Toward semantics-based answer pinpointing
Eduard Hovy, Laurie Gerber, Ulf Hermjakob, Chin-Yew Lin, and Deepak Ravichandran · 2001
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Learning question classifiers
Xin Li and Dan Roth · 2002
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English gigaword
David Graff, Junbo Kong, Ke Chen, and Kazuaki Maeda · 2003
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Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang · 2003
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The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini · 2005
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Automatically constructing a corpus of sentential paraphrases
William B Dolan and Chris Brockett · 2005
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Unifiedqa: Crossing format boundaries with a single QA system
Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, and Hannaneh Hajishirzi · 2005
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Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales
Bo Pang and Lillian Lee · 2005
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The second pascal recognising textual entailment challenge
Roy Bar-Haim, Ido Dagan, Bill Dolan, Lisa Ferro, Danilo Giampiccolo, Bernardo Magnini, and Idan Szpektor · 2006
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The third pascal recognizing textual entailment challenge
Danilo Giampiccolo, Bernardo Magnini, Ido Dagan, and Bill Dolan · 2007
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A unified architecture for natural language processing: deep neural networks with multitask learning
Ronan Collobert and Jason Weston · 2008
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The fifth pascal recognizing textual entailment challenge
Luisa Bentivogli, Peter Clark, Ido Dagan, and Danilo Giampiccolo · 2009
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Twitter sentiment classification using distant supervision
Alec Go, Richa Bhayani, and Lei Huang · 2009
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Learning word vectors for sentiment analysis
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts · 2011
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Choice of plausible alternatives: An evaluation of commonsense causal reasoning
Melissa Roemmele, Cosmin Adrian Bejan, and Andrew S Gordon · 2011
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The winograd schema challenge
Hector Levesque, Ernest Davis, and Leora Morgenstern · 2012
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Semantic parsing on Freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang · 2013
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Hidden factors and hidden topics: understanding rating dimensions with review text
Julian McAuley and Jure Leskovec · 2013
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom · 2015
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Dbpedia–a large-scale, multilingual knowledge base extracted from wikipedia
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick Van Kleef, S”oren Auer, et al · 2015
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A neural attention model for abstractive sentence summarization
Alexander M. Rush, Sumit Chopra, and Jason Weston · 2015
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WikiQA: A Challenge Dataset for Open-Domain Question Answering
Yang Yi, Yih Wen-tau, and Christopher Meek · 2015
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A joint many-task model: Growing a neural network for multiple NLP tasks
Kazuma Hashimoto, Caiming Xiong, Yoshimasa Tsuruoka, and Richard Socher · 2016
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Generating text from structured data with application to the biography domain
Rémi Lebret, David Grangier, and Michael Auli · 2016
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The lambada dataset: Word prediction requiring a broad discourse context
Denis Paperno, Germán Kruszewski, Angeliki Lazaridou, Ngoc-Quan Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda, and Raquel Fernández · 2016
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SQuAD: 100,000+ Questions for Machine Comprehension of Text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
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Crowdsourcing multiple choice science questions
Matt Gardner Johannes Welbl, Nelson F. Liu · 2017
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triviaqa: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer · 2017
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Race: Large-scale reading comprehension dataset from examinations
Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy · 2017
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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning · 2017
Cited alongside, same era.
QuAC: Question answering in context
Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, and Luke Zettlemoyer · 2018
Cited alongside, same era.
Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord · 2018
Cited alongside, same era.
Hate Speech Dataset from a White Supremacy Forum
Ona de Gibert, Naiara Perez, Aitor Garcia-Pablos, and Montse Cuadros · 2018
Cited alongside, same era.
Looking beyond the surface:a challenge set for reading comprehension over multiple sentences
Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay, and Dan Roth · 2018
Cited alongside, same era.
Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, and Yejin Choi · 2020
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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, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris 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
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UNIFIEDQA: Crossing format boundaries with a single QA system
Daniel Khashabi, Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, and Hannaneh Hajishirzi · 2020
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Qasc: A dataset for question answering via sentence composition
Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, and Ashish Sabharwal · 2020
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CommonGen: A constrained text generation challenge for generative commonsense reasoning
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The natural language decathlon: Multitask learning as question answering
Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, and Richard Socher · 2018
Cited alongside, same era.
Can a suit of armor conduct electricity? a new dataset for open book question answering
Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal · 2018
Cited alongside, same era.
Shashi Narayan, Shay B. Cohen, and Mirella Lapata · 2018
Cited alongside, same era.
Wic: 10, 000 example pairs for evaluating context-sensitive representations
Mohammad Taher Pilehvar and os’e Camacho-Collados · 2018
Cited alongside, same era.
Collecting diverse natural language inference problems for sentence representation evaluation
Adam Poliak, Aparajita Haldar, Rachel Rudinger, J. Edward Hu, Ellie Pavlick, Aaron Steven White, and Benjamin Van Durme · 2018
Cited alongside, same era.
Gender bias in coreference resolution
Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme · 2018
Cited alongside, same era.
DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension
Amrita Saha, Rahul Aralikatte, Mitesh M. Khapra, and Karthik Sankaranarayanan · 2018
Cited alongside, same era.
Bill Yuchen Lin, Wangchunshu Zhou, Ming Shen, Pei Zhou, Chandra Bhagavatula, Yejin Choi, and Xiang Ren · 2020
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CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models
Nikita Nangia, Clara Vania, Rasika Bhalerao, and Samuel R. Bowman · 2020
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Adversarial nli: A new benchmark for natural language understanding
Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, and Douwe Kiela · 2020
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Intermediate-task transfer learning with pretrained language models: When and why does it work?
Yada Pruksachatkun, Jason Phang, Haokun Liu, Phu Mon Htut, Xiaoyi Zhang, Richard Yuanzhe Pang, Clara Vania, Katharina Kann, and Samuel R. Bowman · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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How much knowledge can you pack into the parameters of a language model?
Adam Roberts, Colin Raffel, and Noam Shazeer · 2020
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Getting closer to AI complete question answering: A set of prerequisite real tasks
Anna Rogers, Olga Kovaleva, Matthew Downey, and Anna Rumshisky · 2020
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Green ai
Roy Schwartz, Jesse Dodge, Noah A Smith, and Oren Etzioni · 2020
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Exploring and predicting transferability across NLP tasks
Tu Vu, Tong Wang, Tsendsuren Munkhdalai, Alessandro Sordoni, Adam Trischler, Andrew Mattarella-Micke, Subhransu Maji, and Mohit Iyyer · 2020
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Anlizing the adversarial natural language inference dataset
Adina Williams, Tristan Thrush, and Douwe Kiela · 2020
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On the dangers of stochastic parrots: Can language models be too big?
Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell · 2021
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Beyond the imitation game: Measuring and extrapolating the capabilities of language models
BIG-bench collaboration · 2021
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, and et al · 2021
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A framework for few-shot language model evaluation, September 2021
Leo Gao, Jonathan Tow, Stella Biderman, Sid Black, Anthony DiPofi, Charles Foster, Laurence Golding, Jeffrey Hsu, Kyle McDonell, Niklas Muennighoff, Jason Phang, Laria Reynolds, Eric Tang, Anish Thite, Ben Wang, Kevin Wang, and Andy Zou · 2021
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Boseop Kim, HyoungSeok Kim, Sang-Woo Lee, Gichang Lee, Donghyun Kwak, Dong Hyeon Jeon, Sunghyun Park, Sungju Kim, Seonhoon Kim, Dongpil Seo, et al · 2021
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Deduplicating training data makes language models better
Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, and Nicholas Carlini · 2021
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant · 2021
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Datasets: A community library for natural language processing
Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, Abhishek Thakur, Patrick von Platen, Suraj Patil, Julien Chaumond, Mariama Drame, Julien Plu, Lewis Tunstall, Joe Davison, Mario Šaško, Gunjan Chhablani, Bhavitvya Malik, Simon Brandeis, Teven Le Scao, Victor Sanh, Canwen Xu, Nicolas Patry, Angelina McMillan-Major, Philipp Schmid, Sylvain Gugger, Clément Delangue, Théo Matussière, Lysandre Debut, Stas Bekman, Pierric Cistac, Thibault Goehringer, Victor Mustar, François Lagunas, Alexander M. Rush, and Thomas Wolf · 2021
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Cutting down on prompts and parameters: Simple few-shot learning with language models
Robert L Logan, Ivana Balažević, Eric Wallace, Fabio Petroni, Sameer Singh, and Sebastian Riedel · 2021
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Natural instructions: Benchmarking generalization to new tasks from natural language instructions
Swaroop Mishra, Daniel Khashabi, Chitta Baral, and Hannaneh Hajishirzi · 2021
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Carbon emissions and large neural network training
David Patterson, Joseph Gonzalez, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David So, Maud Texier, and Jeff Dean · 2021
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True few-shot learning with language models
Ethan Perez, Douwe Kiela, and Kyunghyun Cho · 2021
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Prompt programming for large language models: Beyond the few-shot paradigm
Laria Reynolds and Kyle McDonell · 2021
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Exploiting cloze-questions for few-shot text classification and natural language inference
Timo Schick and Hinrich Schütze · 2021
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Entailment as few-shot learner
Sinong Wang, Han Fang, Madian Khabsa, Hanzi Mao, and Hao Ma · 2021
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Do prompt-based models really understand the meaning of their prompts?, 2021
Albert Webson and Ellie Pavlick · 2021
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Finetuned language models are zero-shot learners, 2021
Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le · 2021
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Crossfit: A few-shot learning challenge for cross-task generalization in nlp
Qinyuan Ye, Bill Yuchen Lin, and Xiang Ren · 2021
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Calibrate before use: Improving few-shot performance of language models, 2021
Tony Z. Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh · 2021
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Adapting language models for zero-shot learning by meta-tuning on dataset and prompt collections
Ruiqi Zhong, Kristy Lee, Zheng Zhang, and Dan Klein · 2021
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Promptsource: An integrated development environment and repository for natural language prompts, 2022
Stephen H. Bach, Victor Sanh, Zheng-Xin Yong, Albert Webson, Colin Raffel, Nihal V. Nayak, Abheesht Sharma, Taewoon Kim, M Saiful Bari, Thibault Fevry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-David, Canwen Xu, Gunjan Chhablani, Han Wang, Jason Alan Fries, Maged S. Al-shaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Xiangru Tang, Mike Tian-Jian Jiang, and Alexander M. Rush · 2022
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