3 papers
cs.AI2026
stable-worldmodel-v1: Reproducible World Modeling Research and Evaluation
Lucas Maes, Quentin Le Lidec, Dan Haramati +4
World Models have emerged as a powerful paradigm for learning compact, predictive representations of environment dynamics, enabling agents to reason, plan, and generalize beyond di…
cs.SE2025
stable-pretraining-v1: Foundation Model Research Made Simple
Randall Balestriero, Hugues Van Assel, Sami BuGhanem +1
Foundation models and self-supervised learning (SSL) have become central to modern AI, yet research in this area remains hindered by complex codebases, redundant re-implementations…
cs.LG2024
Understanding Adam Requires Better Rotation Dependent Assumptions
Tianyue H. Zhang, Lucas Maes, Alan Milligan +5
Despite its widespread adoption, Adam's advantage over Stochastic Gradient Descent (SGD) lacks a comprehensive theoretical explanation. This paper investigates Adam's sensitivity t…