DS-VLA: A Dendritic-inspired Vision-Language-Action Model for Robust Action Control
Vision-language-action (VLA) models have achieved strong performance in language-conditioned manipulation, yet success under nominal evaluation does not necessarily translate into robust closed-loop behavior when executed actions are transiently corrupted. We introduce DS-VLA, a dendritic-inspired action architecture that incorporates dendritic spiking dynamics into VLA control to address this limitation. Specifically, to enable modularized feature processing and temporal information integration, DS-VLA equips action neurons with multiple sparsely connected dendritic branches, each featuring heterogeneous, learned decay factors. Furthermore, to suppress unreliable state updates while pres...
| Authors | Yaxing Lyu, Jingyi Li, Mingkun Xu et al. |
|---|---|
| Primary category | cs.RO |
| Published | 26 September 2026 |
| Last updated at source | 26 September 2026 |
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