7 papers
RDGen: Demonstration Generation for High-Quality Robot Learning via Reinforcement Learning
Zijian Zhu, Menglin Zou, Zhuang Li +2
Vision-Language-Action (VLA) models have emerged as a promising paradigm for general-purpose robot control. However, their performance remains fundamentally constrained by the avai…
ROI-Driven Foveated Attention for Unified Egocentric Representations in Vision-Language-Action Systems
Xinhai Sun, Xiang Shi, Menglin Zou +1
The development of embodied AI systems is increasingly constrained by the availability and structure of physical interaction data. Despite recent advances in vision-language-action…
Beyond-Ten-Hour Coherence in a Decoherence-Free Trapped-Ion Clock Qubit
Jiahao Pi, Xiangjia Liu, Junle Cao +8
Quantum systems promise to revolutionize information processing science and technology [1-3]. The preservation of quantum coherence, the defining property of qubits, fundamentally…
SaiVLA-0: Cerebrum--Pons--Cerebellum Tripartite Architecture for Compute-Aware Vision-Language-Action
Xiang Shi, Wenlong Huang, Menglin Zou +1
We revisit Vision-Language-Action through a neuroscience-inspired triad. Biologically, the Cerebrum provides stable high-level multimodal priors and remains frozen; the Pons Adapte…
Realization of Trapped Ion Dynamics in the Strong-Field Regime and Non-Markovianity
Kamran Rehan, Hengchao Tu, Tadeu Tassis +5
Probing quantum dynamics in the strong-field regime is critical for advancing our understanding of controlled quantum systems and developing robust quantum technologies. In this wo…
Trust Region Reward Optimization and Proximal Inverse Reward Optimization Algorithm
Yang Chen, Menglin Zou, Jiaqi Zhang +6
Inverse Reinforcement Learning (IRL) learns a reward function to explain expert demonstrations. Modern IRL methods often use the adversarial (minimax) formulation that alternates b…