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Jury Learning: Integrating Dissenting Voices into Machine Learning Models


Feb 07, 2022
Mitchell L. Gordon, Michelle S. Lam, Joon Sung Park, Kayur Patel, Jeffrey T. Hancock, Tatsunori Hashimoto, Michael S. Bernstein

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* To appear at CHI 2022 

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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

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

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My Team Will Go On: Differentiating High and Low Viability Teams through Team Interaction


Nov 03, 2020
Hancheng Cao, Vivian Yang, Victor Chen, Yu Jin Lee, Lydia Stone, N'godjigui Junior Diarrassouba, Mark E. Whiting, Michael S. Bernstein

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* Proc. ACM Hum.-Comput. Interact. 4, CSCW3, Article 230 (December 2020) 
* CSCW 2020 Honorable Mention Award 

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Establishing an Evaluation Metric to Quantify Climate Change Image Realism


Oct 22, 2019
Sharon Zhou, Alexandra Luccioni, Gautier Cosne, Michael S. Bernstein, Yoshua Bengio

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* Accepted to the NeurIPS 2019 Workshop, Tackling Climate Change with Machine Learning 

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HYPE: Human eYe Perceptual Evaluation of Generative Models


Apr 24, 2019
Sharon Zhou, Mitchell Gordon, Ranjay Krishna, Austin Narcomey, Durim Morina, Michael S. Bernstein

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* https://hype.stanford.edu 

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A Glimpse Far into the Future: Understanding Long-term Crowd Worker Quality


Nov 01, 2016
Kenji Hata, Ranjay Krishna, Li Fei-Fei, Michael S. Bernstein

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* 10 pages, 11 figures, accepted CSCW 2017 

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Shirtless and Dangerous: Quantifying Linguistic Signals of Gender Bias in an Online Fiction Writing Community


Mar 29, 2016
Ethan Fast, Tina Vachovsky, Michael S. Bernstein

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* in ICWSM 2016 

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