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The past decade has witnessed dramatic gains in natural language processing and an unprecedented scaling of large language models.
Note on the Sampling Error of the Difference between Correlated Proportions or Percentages
Quinn McNemar · 1947
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A Coefficient of Agreement for Nominal Scales
Jacob Cohen · 1960
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Yoda-Speak: A Study of Yoda’s Speaking Pattern and Their Frequencies
Michael Kaminski · 2011
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English VP-fronting and the Syntax of Yoda
George Walkden · 2012
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A Systemic Functional Translation Analysis of Thematic Structure: Directing Attention to Yoda’s Linguistic Manifestation
Elaine Espindola · 2016
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“Why Should I Trust You?”: Explaining the Predictions of Any Classifier
Marco Túlio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
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In-Datacenter Performance Analysis of a Tensor Processing Unit
Norman P. Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Al Borchers, Rick Boyle, Pierre-luc Cantin, Clifford Chao, Chris Clark, Jeremy Coriell, Mike Daley, Matt Dau, Jeffrey Dean, Ben Gelb, Tara Vazir Ghaemmaghami, Rajendra Gottipati, William Gulland, Robert Hagmann, C. Richard Ho, Doug Hogberg, John Hu, Robert Hundt, Dan Hurt, Julian Ibarz, Aaron Jaffey, Alek Jaworski, Alexander Kaplan, Harshit Khaitan, Daniel Killebrew, Andy Koch, Naveen Kumar, Steve Lacy, James Laudon, James Law, Diemthu Le, Chris Leary, Zhuyuan Liu, Kyle Lucke, Alan Lundin, Gordon MacKean, Adriana Maggiore, Maire Mahony, Kieran Miller, Rahul Nagarajan, Ravi Narayanaswami, Ray Ni, Kathy Nix, Thomas Norrie, Mark Omernick, Narayana Penukonda, Andy Phelps, Jonathan Ross, Matt Ross, Amir Salek, Emad Samadiani, Chris Severn, Gregory Sizikov, Matthew Snelham, Jed Souter, Dan Steinberg, Andy Swing, Mercedes Tan, Gregory Thorson, Bo Tian, Horia Toma, Erick Tuttle, Vijay Vasudevan, Richard Walter, Walter Wang, Eric Wilcox, and Doe Hyun Yoon · 2017
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Building Machines that Learn and Think Like People
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, and Samuel J Gershman · 2017
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Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems
Wang Ling, Dani Yogatama, Chris Dyer, and Phil Blunsom · 2017
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A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg and Su-In Lee · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Taku Kudo and John Richardson · 2018
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MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
Aida Amini, Saadia Gabriel, Shanchuan Lin, Rik Koncel-Kedziorski, Yejin Choi, and Hannaneh Hajishirzi · 2019
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Counterfactual Visual Explanations
Yash Goyal, Ziyan Wu, Jan Ernst, Dhruv Batra, Devi Parikh, and Stefan Lee · 2019
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The Curious Case of Neural Text Degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi · 2019
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Sarthak Jain and Byron C. Wallace · 2019
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The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations
Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Xavier Renard, and Marcin Detyniecki · 2019
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Explain Yourself! Leveraging Language Models for Commonsense Reasoning
Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, and Richard Socher · 2019
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Energy and Policy Considerations for Deep Learning in NLP
Emma Strubell, Ananya Ganesh, and Andrew McCallum · 2019
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Improving Machine Reading Comprehension with General Reading Strategies
Kai Sun, Dian Yu, Dong Yu, and Claire Cardie · 2019
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Attention is not not Explanation
Sarah Wiegreffe and Yuval Pinter · 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, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey 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
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Towards Faithfully Interpretable NLP Systems: How Should We Define and Evaluate Faithfulness?
Alon Jacovi and Yoav Goldberg · 2020
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Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning
Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, and Jennifer Wortman Vaughan · 2020
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Explaining Machine Learning Classifiers Through Diverse Counterfactual Explanations
Ramaravind K Mothilal, Amit Sharma, and Chenhao Tan · 2020
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FACE: Feasible and Actionable Counterfactual Explanations
Rafael Poyiadzi, Kacper Sokol, Raul Santos-Rodriguez, Tijl De Bie, and Peter Flach · 2020
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Learning to Deceive with Attention-Based Explanations
Danish Pruthi, Mansi Gupta, Bhuwan Dhingra, Graham Neubig, and Zachary C. Lipton · 2020
Cited alongside, same era.
Unsupervised Commonsense Question Answering with Self-Talk
Vered Shwartz, Peter West, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi · 2020
Cited alongside, same era.
Counterfactual Explanations for Machine Learning: A Review
Sahil Verma, John Dickerson, and Keegan Hines · 2020
Cited alongside, same era.
Generalizing from a few Examples: A Survey on Few-shot Learning
Yaqing Wang, Quanming Yao, James T Kwok, and Lionel M Ni · 2020
Cited alongside, same era.
A Survey on the Explainability of Supervised Machine Learning
Nadia Burkart and Marco F Huber · 2021
Cited alongside, same era.
Finetuned Language Models are Zero-shot Learners
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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Relating Transformers to Models and Neural Representations of the Hippocampal Formation
James CR Whittington, Joseph Warren, and Tim EJ Behrens · 2021
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An Explanation of In-context Learning as Implicit Bayesian Inference
Sang Michael Xie, Aditi Raghunathan, Percy Liang, and Tengyu Ma · 2021
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Do as I Can, not as I Say: Grounding Language in Robotic Affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Chuyuan Fu, Keerthana Gopalakrishnan, Karol Hausman, Alex Herzog, Daniel Ho, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan, and Andy Zeng · 2022
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Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman · 2021
Cited alongside, same era.
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond
Amir Feder, Katherine A. Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E. Roberts, Brandon M. Stewart, Victor Veitch, and Diyi Yang · 2021
Cited alongside, same era.
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, Pawan Sasanka Ammanamanchi, Aremu Anuoluwapo, Antoine Bosselut, Khyathi Raghavi Chandu, Miruna Clinciu, Dipanjan Das, Kaustubh D. Dhole, Wanyu Du, Esin Durmus, Ondřej Dušek, Chris Emezue, Varun Gangal, Cristina Garbacea, Tatsunori Hashimoto, Yufang Hou, Yacine Jernite, Harsh Jhamtani, Yangfeng Ji, Shailza Jolly, Mihir Kale, Dhruv Kumar, Faisal Ladhak, Aman Madaan, Mounica Maddela, Khyati Mahajan, Saad Mahamood, Bodhisattwa Prasad Majumder, Pedro Henrique Martins, Angelina McMillan-Major, Simon Mille, Emiel van Miltenburg, Moin Nadeem, Shashi Narayan, Vitaly Nikolaev, Rubungo Andre Niyongabo, Salomey Osei, Ankur Parikh, Laura Perez-Beltrachini, Niranjan Ramesh Rao, Vikas Raunak, Juan Diego Rodriguez, Sashank Santhanam, João Sedoc, Thibault Sellam, Samira Shaikh, Anastasia Shimorina, Marco Antonio Sobrevilla Cabezudo, Hendrik Strobelt, Nishant Subramani, Wei Xu, Diyi Yang, Akhila Yerukola, and Jiawei Zhou · 2021
Cited alongside, same era.
Ten Lessons from Three Generations Shaped Google’s TPUv4i: Industrial Product
Norman P. Jouppi, Doe Hyun Yoon, Matthew Ashcraft, Mark Gottscho, Thomas B. Jablin, George Kurian, James Laudon, Sheng Li, Peter Ma, Xiaoyu Ma, Thomas Norrie, Nishant Patil, Sushma Prasad, Cliff Young, Zongwei Zhou, and David Patterson · 2021
Cited alongside, same era.
BeliefBank: Adding Memory to a Pre-Trained Language Model for a Systematic Notion of Belief
Nora Kassner, Oyvind Tafjord, Hinrich Schütze, and Peter Clark · 2021
Cited alongside, same era.
How Many Data Points is a Prompt Worth?
Teven Le Scao and Alexander M Rush · 2021
Cited alongside, same era.
Think about it! Improving Defeasible Reasoning by First Modeling the Question Scenario
Aman Madaan, Niket Tandon, Dheeraj Rajagopal, Peter Clark, Yiming Yang, and Eduard Hovy · 2021
Cited alongside, same era.
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Beyond the Imitation Game: Quantifying and Extrapolating the Capabilities of Language Models
BIG-bench Collaboration · 2022
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Using Cognitive Psychology to Understand GPT-3
Marcel Binz and Eric Schulz · 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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DREAM: Improving Situational QA by First Elaborating the Situation
Yuling Gu, Bhavana Dalvi, and Peter Clark · 2022
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Human-like Property Induction is a Challenge for Large Language Models
Simon Jerome Han, Keith Ransom, Andrew Perfors, and Charles Kemp · 2022
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A Hierarchy of Linguistic Predictions During Natural Language Comprehension
Micha Heilbron, Kristijan Armeni, Jan-Mathijs Schoffelen, Peter Hagoort, and Floris P De Lange · 2022
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Correct Grammar, Yoda’s Speech Is?
Curtis Honeycutt · 2022
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Star Wars: Episode V - The Empire Strikes Back
IMDB · 2022
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Ground-Truth Labels Matter: A Deeper Look into Input-Label Demonstrations
Junyeob Kim, Hyuhng Joon Kim, Hyunsoo Cho, Hwiyeol Jo, Sang-Woo Lee, Sang-goo Lee, Kang Min Yoo, and Taeuk Kim · 2022
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Large Language Models are Zero-Shot Reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
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Solving Quantitative Reasoning Problems with Language Models
Aitor Lewkowycz, Anders Andreassen, David Dohan, Ethan Dyer, Henryk Michalewski, Vinay Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur, Guy Gur-Ari, and Vedant Misra · 2022
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Competition-Level Code Generation with AlphaCode
Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d’Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, and Oriol Vinyals · 2022
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Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
Yao Lu, Max Bartolo, Alastair Moore, Sebastian Riedel, and Pontus Stenetorp · 2022
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Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer · 2022
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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 Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe · 2022
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YODA’S Syntax the Tribune Analyzes; Supply more Details I Will!
Geoffrey K. Pullum · 2022
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Impact of Pretraining Term Frequencies on Few-shot Reasoning
Yasaman Razeghi, Robert L Logan IV, Matt Gardner, and Sameer Singh · 2022
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LaMDA: Language Models for Dialog Applications
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Vincent Zhao, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Pranesh Srinivasan, Laichee Man, Kathleen Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed Chi, and Quoc Le · 2022
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Chain of Thought Prompting Elicits Reasoning in Large Language Models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou · 2022
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Autoformalization with Large Language Models
Yuhuai Wu, Albert Q Jiang, Wenda Li, Markus N Rabe, Charles Staats, Mateja Jamnik, and Christian Szegedy · 2022
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Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, and Ed Chi · 2022
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