5 papers
DexNinja: Learning Robust Dexterous Cutting Policy with a Real-to-Sim-to-Real Data Engine
Haozhe Lou, Runyi Yang, Wanqi Zhong +10
Cutting a piece of food looks effortless in human hands. For a robot, however, every cut is a high-contact interaction with a deformable, elasto-plastic object whose behavior chang…
SkillX: Unified Multi-Skill Policy Learning for Humanoid Soccer
Zhangchen Ye, Enxuan Ruan, Yifei Bao +10
Humanoid soccer is a challenging testbed for dynamic whole-body control, requiring robots to coordinate balance, locomotion, object interaction, and skill switching over long horiz…
Miles v0.1: Production-Level Post-Training
RadixArk, :, Tom Chen +11
We present Miles v0.1, a full-stack, production-ready system for frontier post-training. Building upon the clean design of slime, Miles designs each stage of the reinforcement-lear…
TrojanWorld: Backdooring World-Model Agents via Imagination Steering
Wenkai Huang, Siyuan Liang, Gaolei Li +4
World models increasingly serve as the predictive core of model-based reinforcement learning agents, enabling them to simulate future dynamics and reason over imagined trajectories…
LayerRoute: Action-Conditioned Mixture-of-Layers Routing for Vision-Language-Action Policies
Zheng Lu, Zirong Song, Haoran Liao +11
Vision-Language-Action (VLA) policies leverage pretrained vision-language models (VLMs) to guide action generation for robot control. VLMs provide hierarchical visual-semantic repr…