SpikeVLA replaces transformer components in VLA models with spiking vision encoder, multi-modal LLM, and action policy network to reduce energy consumption while maintaining competitive performance on navigation tasks.
Differential coding for training-free ann-to-snn conversion,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
SDQN-RMFS trains an ANN policy with collision-allowing RL then converts it via hard-label knowledge distillation to an SNN for neuromorphic hardware, reporting up to 11,281× energy savings and 2× lower latency in RMFS pathfinding.
citing papers explorer
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SpikeVLA: Vision-Language-Action Models with Spiking Neural Networks
SpikeVLA replaces transformer components in VLA models with spiking vision encoder, multi-modal LLM, and action policy network to reduce energy consumption while maintaining competitive performance on navigation tasks.
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A Neuromorphic Reinforcement Learning Framework for Efficient Pathfinding in Robotic Mobile Fulfillment Systems
SDQN-RMFS trains an ANN policy with collision-allowing RL then converts it via hard-label knowledge distillation to an SNN for neuromorphic hardware, reporting up to 11,281× energy savings and 2× lower latency in RMFS pathfinding.