Pillar: A Versatile and Extensible Lightweight Markup Language. - Thibault Arloing; Yann Dubois; Stéphane Ducasse; Damien Cassou (IWST, 2016)

Location Attention for Extrapolation to Longer Sequences. - Yann Dubois; Gautier Dagan; Dieuwke Hupkes; Elia Bruni (ACL, 2020)

Convolutional Conditional Neural Processes. - Jonathan Gordon 003; Wessel P. Bruinsma; Andrew Y. K. Foong; James Requeima; Yann Dubois; Richard E. Turner (ICLR, 2020)

Learning Optimal Representations with the Decodable Information Bottleneck. - Yann Dubois; Douwe Kiela; David J. Schwab; Ramakrishna Vedantam (NeurIPS, 2020)

Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes. - Andrew Y. K. Foong; Wessel P. Bruinsma; Jonathan Gordon 003; Yann Dubois; James Requeima; Richard E. Turner (NeurIPS, 2020)

Lossy Compression for Lossless Prediction. - Yann Dubois; Benjamin Bloem-Reddy; Karen Ullrich; Chris J. Maddison (NeurIPS, 2021)

Optimal Representations for Covariate Shift. - Yangjun Ruan; Yann Dubois; Chris J. Maddison (ICLR, 2022)

Improving Self-Supervised Learning by Characterizing Idealized Representations. - Yann Dubois; Stefano Ermon; Tatsunori B. Hashimoto; Percy Liang (NeurIPS, 2022)

Learning Instance-Specific Data Augmentations. - Ning Miao; Emile Mathieu; Yann Dubois; Tom Rainforth; Yee Whye Teh; Adam Foster 001; Hyunjik Kim (CoRR, 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)

Is a Caption Worth a Thousand Images? A Study on Representation Learning. - Shibani Santurkar; Yann Dubois; Rohan Taori; Percy Liang; Tatsunori Hashimoto (ICLR, 2023)

Evaluating Self-Supervised Learning via Risk Decomposition. - Yann Dubois; Tatsunori Hashimoto; Percy Liang (ICML, 2023)

Learning Instance-Specific Augmentations by Capturing Local Invariances. - Ning Miao; Tom Rainforth; Emile Mathieu; Yann Dubois; Yee Whye Teh; Adam Foster 001; Hyunjik Kim (ICML, 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 (NeurIPS, 2023)

AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. - Yann Dubois; Xuechen Li 005; Rohan Taori; Tianyi Zhang; Ishaan Gulrajani; Jimmy Ba; Carlos Guestrin; Percy Liang; Tatsunori B. Hashimoto (CoRR, 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 (ICLR, 2024)

Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators. - Yann Dubois; Balázs Galambosi; Percy Liang; Tatsunori B. Hashimoto (CoRR, 2024)

Learning to (Learn at Test Time): RNNs with Expressive Hidden States. - Yu Sun 020; Xinhao Li; Karan Dalal; Jiarui Xu; Arjun Vikram; Genghan Zhang; Yann Dubois; Xinlei Chen; Xiaolong Wang 004; Sanmi Koyejo; Tatsunori Hashimoto; Carlos Guestrin (CoRR, 2024)

Apollo: An Exploration of Video Understanding in Large Multimodal Models. - Orr Zohar; Xiaohan Wang; Yann Dubois; Nikhil Mehta 002; Tong Xiao; Philippe Hansen-Estruch; Licheng Yu; Xiaofang Wang; Felix Juefei-Xu; Ning Zhang; Serena Yeung-Levy; Xide Xia (CVPR, 2025)