Separating the World and Ego Models for Self-Driving. - Vlad Sobal; Alfredo Canziani; Nicolas Carion; Kyunghyun Cho; Yann LeCun (CoRR, 2022)

Joint Embedding Predictive Architectures Focus on Slow Features. - Vlad Sobal; Jyothir S. V; Siddhartha Jalagam; Nicolas Carion; Kyunghyun Cho; Yann LeCun (CoRR, 2022)

A Cookbook of Self-Supervised Learning. - Randall Balestriero; Mark Ibrahim; Vlad Sobal; Ari Morcos; Shashank Shekhar; Tom Goldstein; Florian Bordes; Adrien Bardes; Grégoire Mialon; Yuandong Tian; Avi Schwarzschild; Andrew Gordon Wilson; et al. (CoRR, 2023)

Gradient-based Planning with World Models. - Jyothir S. V; Siddhartha Jalagam; Yann LeCun; Vlad Sobal (CoRR, 2023)

Light-weight Probing of Unsupervised Representations for Reinforcement Learning. - Wancong Zhang; Anthony GX-Chen; Vlad Sobal; Yann LeCun; Nicolas Carion (RLJ, 2024)

Hierarchical World Models as Visual Whole-Body Humanoid Controllers. - Nicklas Hansen 001; Jyothir S. V; Vlad Sobal; Yann LeCun; Xiaolong Wang 004; Hao Su 001 (ICLR, 2025)

X-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. - Vlad Sobal; Mark Ibrahim; Randall Balestriero; Vivien Cabannes; Diane Bouchacourt; Pietro Astolfi; Kyunghyun Cho; Yann LeCun (ICLR, 2025)

Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models. - Vlad Sobal; Wancong Zhang; Kynghyun Cho; Randall Balestriero; Tim G. J. Rudner; Yann LeCun (CoRR, 2025)