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cs.RO2026
Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training
Yaxuan Li, Zhongyi Zhou, Yefei Chen +5
Post-training is essential for turning pretrained generalist robot policies into reliable task-specific controllers, but existing human-in-the-loop pipelines remain tied to physica…
cs.RO2026
dWorldEval: Scalable Robotic Policy Evaluation via Discrete Diffusion World Model
Yaxuan Li, Zhongyi Zhou, Yefei Chen +2
Evaluating robotics policies across thousands of environments and thousands of tasks is infeasible with existing approaches. This motivates the need for a new methodology for scala…
cs.LG2026
Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe
Yaxuan Li, Yuxin Zuo, Bingxiang He +8
On-policy distillation (OPD) has become a core technique in the post-training of large language models, yet its training dynamics remain poorly understood. This paper provides a sy…