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We present the results of the NLP Community Metasurvey.
Risks from learned optimization in advanced machine learning systems, 2019
Evan Hubinger, Chris van Merwijk, Vladimir Mikulik, Joar Skalse, and Scott Garrabrant · 1906
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Economists’ views about parameters, values, and policies: Survey results in labor and public economics
Victor R Fuchs, Alan B Krueger, and James M Poterba · 1998
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Why most published research findings are false
John P. A. Ioannidis · 2005
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A matter of opinion—How ecological and neoclassical environmental economists and think about sustainability and economics
Lydia Illge and Reimund Schwarze · 2009
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What is economics? Attitudes and views of German economists
Bruno S Frey, Silke Humbert, and Friedrich Schneider · 2010
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Superintelligence: Paths, Dangers, Strategies
Nick Bostrom · 2014
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What do philosophers believe?
David Bourget and David J. Chalmers · 2014
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Concrete problems in ai safety, 2016
Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, and Dan Mané · 2016
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Yes, we care! Results of the ethics and natural language processing surveys
Karën Fort and Alain Couillault · 2016
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Surveying the attitudes of physicists concerning foundational issues of quantum mechanics
Sujeevan Sivasundaram and Kristian Hvidtfelt Nielsen · 2016
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Physiognomy’s new clothes, May 2017
Blaise Agüera y Arcas, Margaret Mitchell, and Alexander Todorov · 2017
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Report on ACL survey on preprint publishing and reviewing
Jennifer Foster, Marti Hearst, Joakim Nivre, and Shiqi Zhao · 2017
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Pathologies of neural models make interpretations difficult
Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, and Jordan Boyd-Graber · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Attention is not Explanation
Sarthak Jain and Byron C. Wallace · 2019
Cited alongside, same era.
The state of NLP literature: A diachronic analysis of the ACL Anthology
Saif M. Mohammad · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Cited alongside, same era.
The bitter lesson, 2019
Rich Sutton · 2019
Cited alongside, same era.
Attention is not not explanation
Sarah Wiegreffe and Yuval Pinter · 2019
Cited alongside, same era.
Climbing towards NLU: On meaning, form, and understanding in the age of data
Emily M. Bender and Alexander Koller · 2020
Cited alongside, same era.
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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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, S. Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen A. Creel, Jared Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren E. 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 F. Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, O. Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir P. Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Benjamin Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, J. F. Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Robert Reich, Hongyu Ren, Frieda Rong, Yusuf H. Roohani, Camilo Ruiz, Jack Ryan, Christopher R’e, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishna Parasuram Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei A. Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, and Percy Liang · 2021
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What will it take to fix benchmarking in natural language understanding?
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David Bourget and David J. Chalmers · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Lessons from the PULSE model and discussion
Andrey Kurenkov · 2020
Cited alongside, same era.
Examining citations of natural language processing literature
Saif M. Mohammad · 2020
Cited alongside, same era.
NLP scholar: A dataset for examining the state of NLP research
Saif M. Mohammad · 2020
Cited alongside, same era.
Gender gap in natural language processing research: Disparities in authorship and citations
Saif M. Mohammad · 2020
Cited alongside, same era.
Samuel R. Bowman and George Dahl · 2021
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Provable Limitations of Acquiring Meaning from Ungrounded Form: What Will Future Language Models Understand?
William Merrill, Yoav Goldberg, Roy Schwartz, and Noah A. Smith · 2021
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Do transformer modifications transfer across implementations and applications?
Sharan Narang, Hyung Won Chung, Yi Tay, Liam Fedus, Thibault Fevry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, and Colin Raffel · 2021
Later among the works it cites.
AI and the everything in the whole wide world benchmark
Inioluwa Deborah Raji, Emily Denton, Emily M. Bender, Alex Hanna, and Amandalynne Paullada · 2021
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2022 ACL ethics survey, 2022
Lucia Benotti, Mark Drezde, Karën Fort, Pascale Fung, Dirk Hovy, Min-Yen Kan, Jin Dong Kim, Malvina Nissim, and Yulia Tsvetkov · 2022
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On the conception and design of the PhilPapers Survey
David Bourget and David J. Chalmers · 2022
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PaLM: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel · 2022
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Language diversity in our ACL community, 2022
Mona Diab · 2022
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The carbon footprint of machine learning training will plateau, then shrink
David Patterson, Joseph Gonzalez, Urs Hölzle, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, and Jeff Dean · 2022
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Survey on the future of reviewing, 2022
Hinrich Schütze · 2022
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Scaling laws vs model architectures: How does inductive bias influence scaling?
Yi Tay, Mostafa Dehghani, Samira Abnar, Hyung Won Chung, William Fedus, Jinfeng Rao, Sharan Narang, Vinh Q Tran, Dani Yogatama, and Donald Metzler · 2022
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