4 papers
WALL-SS: Scaling Long-horizon World Models via Next-Scale Autoregression
Maeve Zhang, Rain Sun, Xiang Wang +22
Generative world models provide robots with predictive models of how the world evolves under interaction, with growing potential for simulation, planning, policy evaluation, and ro…
DMuon: Efficient Distributed Muon Training with Near-Adam Overhead
Vincent Chen, Starrick Liu, Regis Cheng +8
Matrix-orthogonalization-based optimizers, exemplified by Muon, have demonstrated strong convergence behavior across a wide range of modern deep learning workloads. The matrix-awar…
Igniting VLMs toward the Embodied Space
Andy Zhai, Brae Liu, Bruno Fang +17
While foundation models show remarkable progress in language and vision, existing vision-language models (VLMs) still have limited spatial and embodiment understanding. Transferrin…
Explore Reinforced: Equilibrium Approximation with Reinforcement Learning
Ryan Yu, Mateusz Nowak, Qintong Xie +2
Current approximate Coarse Correlated Equilibria (CCE) algorithms struggle with equilibrium approximation for games in large stochastic environments but are theoretically guarantee…