Yann Dubois - RankMe

30 papers A* 14Journal 15Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Apollo: An Exploration of Video Understanding in Large Multimodal Models. CVPR Orr Zohar, Xiaohan Wang, Yann Dubois, Nikhil Mehta, Tong Xiao, Philippe Hansen-Estruch, Licheng Yu, Xiaofang Wang, Felix Juefei-Xu, Ning Zhang, Serena Yeung-Levy, Xide Xia
2025	A*	`conf`	Learning to (Learn at Test Time): RNNs with Expressive Hidden States. ICML Yu Sun, Xinhao Li, Karan Dalal, Jiarui Xu, Arjun Vikram, Genghan Zhang, Yann Dubois, Xinlei Chen, Xiaolong Wang, Sanmi Koyejo, Tatsunori Hashimoto, Carlos Guestrin
2024	J	`jnl`	Apollo: An Exploration of Video Understanding in Large Multimodal Models. CoRR Orr Zohar, Xiaohan Wang, Yann Dubois, Nikhil Mehta, Tong Xiao, Philippe Hansen-Estruch, Licheng Yu, Xiaofang Wang, Felix Juefei-Xu, Ning Zhang, Serena Yeung-Levy, Xide Xia
2024	A*	`conf`	Identifying the Risks of LM Agents with an LM-Emulated Sandbox. ICLR Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto
2024	J	`jnl`	Learning to (Learn at Test Time): RNNs with Expressive Hidden States. CoRR Yu Sun, Xinhao Li, Karan Dalal, Jiarui Xu, Arjun Vikram, Genghan Zhang, Yann Dubois, Xinlei Chen, Xiaolong Wang, Sanmi Koyejo, Tatsunori Hashimoto, Carlos Guestrin
2024	J	`jnl`	Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators. CoRR Yann Dubois, Balázs Galambosi, Percy Liang, Tatsunori B. Hashimoto
2023	A*	`conf`	AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. NeurIPS Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto
2023	J	`jnl`	AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. CoRR Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto
2023	A*	`conf`	Evaluating Self-Supervised Learning via Risk Decomposition. ICML Yann Dubois, Tatsunori Hashimoto, Percy Liang
2023	J	`jnl`	Evaluating Self-Supervised Learning via Risk Decomposition. CoRR Yann Dubois, Tatsunori Hashimoto, Percy Liang
2023	J	`jnl`	Identifying the Risks of LM Agents with an LM-Emulated Sandbox. CoRR Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto
2023	A*	`conf`	Is a Caption Worth a Thousand Images? A Study on Representation Learning. ICLR Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto
2023	A*	`conf`	Learning Instance-Specific Augmentations by Capturing Local Invariances. ICML Ning Miao, Tom Rainforth, Emile Mathieu, Yann Dubois, Yee Whye Teh, Adam Foster, Hyunjik Kim
2022	A*	`conf`	Improving Self-Supervised Learning by Characterizing Idealized Representations. NeurIPS Yann Dubois, Stefano Ermon, Tatsunori B. Hashimoto, Percy Liang
2022	J	`jnl`	Improving Self-Supervised Learning by Characterizing Idealized Representations. CoRR Yann Dubois, Tatsunori Hashimoto, Stefano Ermon, Percy Liang
2022	J	`jnl`	Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning. CoRR Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto
2022	J	`jnl`	Learning Instance-Specific Data Augmentations. CoRR Ning Miao, Emile Mathieu, Yann Dubois, Tom Rainforth, Yee Whye Teh, Adam Foster, Hyunjik Kim
2022	A*	`conf`	Optimal Representations for Covariate Shift. ICLR Yangjun Ruan, Yann Dubois, Chris J. Maddison
2022	J	`jnl`	Optimal Representations for Covariate Shift. CoRR Yangjun Ruan, Yann Dubois, Chris J. Maddison
2021	A*	`conf`	Lossy Compression for Lossless Prediction. NeurIPS Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison
2021	J	`jnl`	Lossy Compression for Lossless Prediction. CoRR Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison
2020	A*	`conf`	Convolutional Conditional Neural Processes. ICLR Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner
2020	A*	`conf`	Learning Optimal Representations with the Decodable Information Bottleneck. NeurIPS Yann Dubois, Douwe Kiela, David J. Schwab, Ramakrishna Vedantam
2020	J	`jnl`	Learning Optimal Representations with the Decodable Information Bottleneck. CoRR Yann Dubois, Douwe Kiela, David J. Schwab, Ramakrishna Vedantam
2020	A*	`conf`	Location Attention for Extrapolation to Longer Sequences. ACL Yann Dubois, Gautier Dagan, Dieuwke Hupkes, Elia Bruni
2020	A*	`conf`	Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes. NeurIPS Andrew Y. K. Foong, Wessel P. Bruinsma, Jonathan Gordon, Yann Dubois, James Requeima, Richard E. Turner
2020	J	`jnl`	Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes. CoRR Andrew Y. K. Foong, Wessel P. Bruinsma, Jonathan Gordon, Yann Dubois, James Requeima, Richard E. Turner
2019	J	`jnl`	Convolutional Conditional Neural Processes. CoRR Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner
2019	J	`jnl`	Location Attention for Extrapolation to Longer Sequences. CoRR Yann Dubois, Gautier Dagan, Dieuwke Hupkes, Elia Bruni
2016	—	`conf`	Pillar: A Versatile and Extensible Lightweight Markup Language. IWST Thibault Arloing, Yann Dubois, Stéphane Ducasse, Damien Cassou