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Pengteng Li

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#artificial intelligence Preprint Jan 2026

NeuroVLA: A Brain-inspired Embodied Intelligence for Fluid and Fast Reflexive Robotics Control

NeuroVLA is introduced, a brain-inspired architecture that couples a cortical vision-language planner to recurrent cerebellar modulation and a stateful spiking spinal controller that translates semantic intent into actions while incorporating high-frequency proprioceptive and force feedback, maintaining short-term moto...

Wei-Yu Guo, He Zhang, Peng-Teng Li et al. · 0 citations
#robotics Preprint Jul 2026

Source-Lifted Flow Matching for Intervenable Multimodal Imitation

Flow-matching policies are promising for imitation learning because they model complex multimodal action distributions. However, their stochasticity is largely passive: repeated sampling may yield diverse behaviors, but users cannot directly choose among valid continuations from the same state. We propose Source-Lifted...

He Zhang, Ying Sun, Pengteng Li et al. · 0 citations
Preprint Aug 2026

How Should Vision-Language-Action Models Use Proprioceptive State?

Five representative interfaces are implemented -- discrete state prompt, VLM prefix, action prefix, state expert, and feature modulation -- under matched implementation details, and evaluated on 45 atomic tasks spanning three task families plus 20 composite tasks.

Yiren Zhao, Ziyang Chen, Zi-Yang Rao et al. · 0 citations

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