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Play to Grade: Testing Coding Games as Classifying Markov Decision Process


Oct 27, 2021
Allen Nie, Emma Brunskill, Chris Piech

* NeurIPS 2021, 16 pages, 7 figures 

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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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Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users


Apr 27, 2021
Moussa Doumbouya, Lisa Einstein, Chris Piech


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Bandit-PAM: Almost Linear Time $k$-Medoids Clustering via Multi-Armed Bandits


Jun 11, 2020
Mo Tiwari, Martin Jinye Zhang, James Mayclin, Sebastian Thrun, Chris Piech, Ilan Shomorony

* 18 pages 

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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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Human Languages in Source Code: Auto-Translation for Localized Instruction


Sep 10, 2019
Chris Piech, Sami Abu-El-Haija


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The Stanford Acuity Test: A Probabilistic Approach for Precise Visual Acuity Testing


Jun 05, 2019
Chris Piech, Ali Malik, Laura M Scott, Robert T Chang, Charles Lin

* Under review in the journal of Optometry and Vision Science 

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Using Latent Variable Models to Observe Academic Pathways


May 31, 2019
Nate Gruver, Ali Malik, Brahm Capoor, Chris Piech, Mitchell L. Stevens, Andreas Paepcke

* Twelfth International Conference on Educational Data Mining 

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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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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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Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction


Jun 30, 2018
Christina Wadsworth, Francesca Vera, Chris Piech

* To be published in FAT/ML, 2018, Stockholm, Sweden 

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Deep Knowledge Tracing


Jun 19, 2015
Chris Piech, Jonathan Spencer, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas Guibas, Jascha Sohl-Dickstein


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Learning Program Embeddings to Propagate Feedback on Student Code


May 22, 2015
Chris Piech, Jonathan Huang, Andy Nguyen, Mike Phulsuksombati, Mehran Sahami, Leonidas Guibas

* Accepted to International Conference on Machine Learning (ICML 2015) 

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Tuned Models of Peer Assessment in MOOCs


Jul 09, 2013
Chris Piech, Jonathan Huang, Zhenghao Chen, Chuong Do, Andrew Ng, Daphne Koller

* Proceedings of The 6th International Conference on Educational Data Mining (EDM 2013) 

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