Generalist robot policies and language-model agents provide complementary capabilities, but completing a task also requires adapting their use to the consequences of physical interaction. We study execution as a locus of adaptation: feedback guides the current action and supplies evidence for revising subsequent decisi...
He-Yang Yu, Hao-Min Li, Si-Hang Li et al.· 0 citations
Humanoid soccer contact skills require more than producing high-impact foot-ball contacts: the robot must close the loop over perception, approach, alignment, impact, and recovery while its own motion induces substantial viewpoint changes, frequent loss of the ball from view, and uncertain contact outcomes. In this wor...
Jia-Kang Jin, Yi-Xiao Huo, Peng-Yuan Wang et al.· 0 citations
SkillX is presented, a unified reinforcement learning framework that learns and composes multiple atomic soccer skills through a single command-conditioned policy, enabling the robot to execute atomic skills and transition among them such as dribbling, trapping, and shooting.
Zhang-Chen Ye, En-Xuan Ruan, Yi-Fei Bao et al.· 2 citations
A metric interaction framework that models object-level and scene-level interactions in physical Cartesian space at a shared metric scale and improves diverse VLA and WAM baselines with a small number of additional parameters and training steps is introduced.
Li-Jie Wang, Zheng Lu, Yi-Ming Wang et al.· 0 citations
Miles v0.1 is presented, a full-stack, production-ready system for frontier post-training reinforcement-learning training, which supports LoRA RL, on-policy distillation, supervised fine-tuning, and true-on-policy rollout-training alignment, and extends the same architecture to diffusion models.
To achieve effective, stealthy, and persistent control, TrojanWorld combines Decision-Reflective Induction to steer trigger-conditioned imagination toward attacker-specified actions using decision feedback, Clean Behavior Anchoring to preserve trigger-free predictive and behavioral fidelity, and Causal Propagation to s...
Wen-Kai Huang, Si-Yuan Liang, Gaolei Li et al.· 0 citations
Vision-Language-Action (VLA) policies leverage pretrained vision-language models (VLMs) to guide action generation for robot control. VLMs provide hierarchical visual-semantic representations that evolve across layers, from local visual geometry to abstract, language-aligned semantics; different manipulation tasks may...
Zi-Rong Song, Zheng Lu, Hao-Ran Liao et al.· 2 citations
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