Drew A. Hudson

According to our database, Drew A. Hudson authored at least 10 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

SODA: Bottleneck Diffusion Models for Representation Learning.

Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner

CoRR, 2023

2022

Holistic Evaluation of Language Models.

Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

CoRR, 2022

2021

Compositional Transformers for Scene Generation.

Drew A. Hudson, C. Lawrence Zitnick

CoRR, 2021

On the Opportunities and Risks of Foundation Models.

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya 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 D. 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 Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.

CoRR, 2021

Generative Adversarial Transformers.

Drew A. Hudson, Larry Zitnick

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

SLM: Learning a Discourse Language Representation with Sentence Unshuffling.

Haejun Lee, Drew A. Hudson, Kangwook Lee, Christopher D. Manning

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019

GQA: a new dataset for compositional question answering over real-world images.

Drew A. Hudson, Christopher D. Manning

CoRR, 2019

Learning by Abstraction: The Neural State Machine.

Drew A. Hudson, Christopher D. Manning

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering.

Drew A. Hudson, Christopher D. Manning

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Compositional Attention Networks for Machine Reasoning.

Drew A. Hudson, Christopher D. Manning

Proceedings of the 6th International Conference on Learning Representations, 2018