Xiaomeng Zhu

Plan Right, Then Plan Tight: Symbolic RL for Efficient Embodied Reasoning

This work shows that a single BDDL specification, automatically constructed from open-world video evidence or curated tasks, can serve as a shared interface for data construction, plan verification, and reward design and introduces GroupAdapt, a difficulty-aware length schedule that uses the in-batch group pass rate as a zero-cost signal so that hard prompts get wider length tolerance and automatically tighten as their pass rate improves.