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DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning


Nov 23, 2021
Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah Goodman

* NeurIPS 2021, Datasets & Benchmarks Track 

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Open-domain clarification question generation without question examples


Oct 19, 2021
Julia White, Gabriel Poesia, Robert Hawkins, Dorsa Sadigh, Noah Goodman

* EMNLP 2021 

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Temperature as Uncertainty in Contrastive Learning


Oct 08, 2021
Oliver Zhang, Mike Wu, Jasmine Bayrooti, Noah Goodman

* 4 pages content; 1 page supplement 

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Modeling Item Response Theory with Stochastic Variational Inference


Aug 26, 2021
Mike Wu, Richard L. Davis, Benjamin W. Domingue, Chris Piech, Noah Goodman

* 33 pages of content; 5 pages appendix. arXiv admin note: text overlap with arXiv:2002.00276 

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On the Opportunities and Risks of Foundation Models


Aug 18, 2021
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 Chen, Kathleen Creel, Jared Quincy Davis, Dora 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 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 Kohd, Mark 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 Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan 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 Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang

* Authored by the Center for Research on Foundation Models (CRFM) at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) 

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ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback


Jul 23, 2021
Mike Wu, Noah Goodman, Chris Piech, Chelsea Finn

* 9 pages content; 6 pages supplement 

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Contrastive Reinforcement Learning of Symbolic Reasoning Domains


Jun 16, 2021
Gabriel Poesia, WenXin Dong, Noah Goodman


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Question Generation for Adaptive Education


Jun 08, 2021
Megha Srivastava, Noah Goodman

* 10 pages, 3 figures, ACL 2021 

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Emergent Communication of Generalizations


Jun 04, 2021
Jesse Mu, Noah Goodman

* 18 pages 

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Improving Compositionality of Neural Networks by Decoding Representations to Inputs


Jun 01, 2021
Mike Wu, Noah Goodman, Stefano Ermon

* 9 pages content; 2 pages appendix 

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Language Through a Prism: A Spectral Approach for Multiscale Language Representations


Nov 09, 2020
Alex Tamkin, Dan Jurafsky, Noah Goodman

* NeurIPS 2020 

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Viewmaker Networks: Learning Views for Unsupervised Representation Learning


Oct 14, 2020
Alex Tamkin, Mike Wu, Noah Goodman


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A Simple Framework for Uncertainty in Contrastive Learning


Oct 05, 2020
Mike Wu, Noah Goodman

* 8 pages main text 

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Conditional Negative Sampling for Contrastive Learning of Visual Representations


Oct 05, 2020
Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah Goodman

* 8 pages, 4 pages supplement 

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On Mutual Information in Contrastive Learning for Visual Representations


Jun 05, 2020
Mike Wu, Chengxu Zhuang, Milan Mosse, Daniel Yamins, Noah Goodman

* 8 pages content; 15 pages supplement with proofs 

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Investigating Transferability in Pretrained Language Models


Apr 30, 2020
Alex Tamkin, Trisha Singh, Davide Giovanardi, Noah Goodman


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Variational Item Response Theory: Fast, Accurate, and Expressive


Feb 01, 2020
Mike Wu, Richard L. Davis, Benjamin W. Domingue, Chris Piech, Noah Goodman

* 11 pages of content with supplement 

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Multimodal Generative Models for Compositional Representation Learning


Dec 11, 2019
Mike Wu, Noah Goodman

* 24 pages content; 7 pages appendix 

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Shaping Visual Representations with Language for Few-shot Classification


Nov 06, 2019
Jesse Mu, Percy Liang, Noah Goodman

* 9 pages inc. supplement; NeurIPS 2019 Workshop on Visually Grounded Interaction and Language (ViGIL) 

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Generative Grading: Neural Approximate Parsing for Automated Student Feedback


May 23, 2019
Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, John Mitchell, Noah Goodman, Chris Piech

* 8 pages + supplement 

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Lost in Machine Translation: A Method to Reduce Meaning Loss


Apr 12, 2019
Reuben Cohn-Gordon, Noah Goodman

* NAACL short paper 

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Pragmatic inference and visual abstraction enable contextual flexibility during visual communication


Mar 28, 2019
Judith Fan, Robert Hawkins, Mike Wu, Noah Goodman

* 29 pages; 5 figures; submitted draft of manuscript 

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Variational Estimators for Bayesian Optimal Experimental Design


Mar 13, 2019
Adam Foster, Martin Jankowiak, Eli Bingham, Paul Horsfall, Yee Whye Teh, Tom Rainforth, Noah Goodman


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Tensor Variable Elimination for Plated Factor Graphs


Feb 08, 2019
Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Justin Chiu, Neeraj Pradhan, Alexander Rush, Noah Goodman

* 17 pages 

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Meta-Amortized Variational Inference and Learning


Feb 05, 2019
Kristy Choi, Mike Wu, Noah Goodman, Stefano Ermon

* First 2 authors contributed equally 

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Bias and Generalization in Deep Generative Models: An Empirical Study


Nov 08, 2018
Shengjia Zhao, Hongyu Ren, Arianna Yuan, Jiaming Song, Noah Goodman, Stefano Ermon


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Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference


Sep 05, 2018
Mike Wu, Milan Mosse, Noah Goodman, Chris Piech

* 8 pages 

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Multimodal Generative Models for Scalable Weakly-Supervised Learning


May 18, 2018
Mike Wu, Noah Goodman

* 8 pages with supplement 

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