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cs.RO2026
Memory as Plans: World-Action Modeling with Memory-Grounded Planning
Sizhe Zhao, Haozhe Xie, Weiyu Zhao +5
Mainstream robotic policies often adopt a Markovian formulation, but many complex real-world manipulation tasks are inherently non-Markovian, requiring long-horizon memory beyond t…
cs.RO2026
TapSampling: Inference-Time Sampling with a Task-Progress-Understanding Verifier for Robotic Manipulation
Sizhe Zhao, Shengping Zhang, Shuo Yang +3
Existing embodied control research demonstrates remarkable performance improvements by scaling training data and model size. We instead explore inference-time strategy as an altern…