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Training and Inference on Any-Order Autoregressive Models the Right Way


May 26, 2022
Andy Shih, Dorsa Sadigh, Stefano Ermon

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Imitation Learning by Estimating Expertise of Demonstrators


Feb 02, 2022
Mark Beliaev, Andy Shih, Stefano Ermon, Dorsa Sadigh, Ramtin Pedarsani

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* 15 pages 

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Conditional Imitation Learning for Multi-Agent Games


Jan 05, 2022
Andy Shih, Stefano Ermon, Dorsa Sadigh

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* 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2022 

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PantheonRL: A MARL Library for Dynamic Training Interactions


Dec 13, 2021
Bidipta Sarkar, Aditi Talati, Andy Shih, Dorsa Sadigh

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* 3 pages, 3 figures. Published in Proceedings of the 36th AAAI Conference on Artificial Intelligence (Demo Track) 2022 

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HyperSPNs: Compact and Expressive Probabilistic Circuits


Dec 02, 2021
Andy Shih, Dorsa Sadigh, Stefano Ermon

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* In Advances in Neural Information Processing Systems 34 (NeurIPS), 2021 

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Influencing Towards Stable Multi-Agent Interactions


Oct 05, 2021
Woodrow Z. Wang, Andy Shih, Annie Xie, Dorsa Sadigh

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* 15 pages, 5 figures, Published as an Oral at Conference on Robot Learning (CoRL) 2021 

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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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On the Critical Role of Conventions in Adaptive Human-AI Collaboration


Apr 07, 2021
Andy Shih, Arjun Sawhney, Jovana Kondic, Stefano Ermon, Dorsa Sadigh

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* 9th International Conference on Learning Representations (ICLR 2021) 

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Probabilistic Circuits for Variational Inference in Discrete Graphical Models


Oct 22, 2020
Andy Shih, Stefano Ermon

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* In Advances in Neural Information Processing Systems 34 (NeurIPS), 2020 

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