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.
Hyunseok Oh and Youngki Lee
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
SAFA-SNN combines sparsity-aware spike dynamics and orthogonal subspace projection in spiking networks to achieve on-device few-shot class-incremental learning with lower energy use and reduced forgetting than prior baselines.
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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SAFA-SNN: Sparsity-Aware On-Device Few-Shot Class-Incremental Learning with Fast-Adaptive Structure of Spiking Neural Network
SAFA-SNN combines sparsity-aware spike dynamics and orthogonal subspace projection in spiking networks to achieve on-device few-shot class-incremental learning with lower energy use and reduced forgetting than prior baselines.