Yann Dubois

According to our database, Yann Dubois authored at least 16 papers between 2016 and 2023.

Collaborative distances:

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

2023

Identifying the Risks of LM Agents with an LM-Emulated Sandbox.

Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto

CoRR, 2023

AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback.

Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto

CoRR, 2023

AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback.

Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Instance-Specific Augmentations by Capturing Local Invariances.

Ning Miao, Tom Rainforth, Emile Mathieu, Yann Dubois, Yee Whye Teh, Adam Foster, Hyunjik Kim

Proceedings of the International Conference on Machine Learning, 2023

Evaluating Self-Supervised Learning via Risk Decomposition.

Yann Dubois, Tatsunori Hashimoto, Percy Liang

Proceedings of the International Conference on Machine Learning, 2023

Is a Caption Worth a Thousand Images? A Study on Representation Learning.

Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning.

Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto

CoRR, 2022

Learning Instance-Specific Data Augmentations.

Ning Miao, Emile Mathieu, Yann Dubois, Tom Rainforth, Yee Whye Teh, Adam Foster, Hyunjik Kim

CoRR, 2022

Improving Self-Supervised Learning by Characterizing Idealized Representations.

Yann Dubois, Stefano Ermon, Tatsunori B. Hashimoto, Percy Liang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Optimal Representations for Covariate Shift.

Yangjun Ruan, Yann Dubois, Chris J. Maddison

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Lossy Compression for Lossless Prediction.

Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes.

Andrew Y. K. Foong, Wessel P. Bruinsma, Jonathan Gordon, Yann Dubois, James Requeima, Richard E. Turner

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Optimal Representations with the Decodable Information Bottleneck.

Yann Dubois, Douwe Kiela, David J. Schwab, Ramakrishna Vedantam

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Convolutional Conditional Neural Processes.

Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner

Proceedings of the 8th International Conference on Learning Representations, 2020

Location Attention for Extrapolation to Longer Sequences.

Yann Dubois, Gautier Dagan, Dieuwke Hupkes, Elia Bruni

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2016

Pillar: A Versatile and Extensible Lightweight Markup Language.

Thibault Arloing, Yann Dubois, Stéphane Ducasse, Damien Cassou

Proceedings of the 11th edition of the International Workshop on Smalltalk Technologies, 2016