Before deploying runtime recovery for a frozen vision-language-action (VLA) policy, one must establish that an intervention improves success beyond ordinary run-to-run variation and that its complexity adds value over a simple action. We evaluate these questions on frozen $\pi_{0.5}$ across four RoboTwin tasks. For eac...
Chen-Chao Sheng, Zhuang Jiang, Liu Yang et al.· 0 citations
Reinforcement Learning (RL)-based post-training has become a key mechanism for improving reasoning Large Language Models (LLMs), especially when automated verifiers enable Reinforcement Learning with Verifiable Reward (RLVR). Recent methods, however, are increasingly modular: many apparent algorithmic advances recombin...
Liu Yang, Han Zhu, Zheng-Yang Zhong et al.· International Conference on...· 2 citations
Reinforcement learning (RL) has become a central post-training approach for reasoning and agentic large language models (LLMs), particularly when task outcomes can be verified automatically. Comparisons across this literature remain difficult because a reported gain may combine changes to the learning signal, policy co...
Liu Yang, Han Zhu, Zheng-Yang Zhong et al.· Unmanned Systems· 1 citation
WAM-OPD, a deployment-consistent post-training recipe for a video-first WAM, is introduced and it is suggested that dense teacher supervision on student-induced histories is a promising post-training interface for video-first WAMs.
Liu Yang, Zhuang Jiang, Chenchao Sheng et al.· 2 citations
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