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Frequency domain analysis unlocks 1.59x speedups in Vision-Language-Navigation by enabling optimal token caching, a feat previously limited by visual domain approaches.
Robots can think (and act) twice as fast: HeiSD's hybrid speculative decoding turbocharges embodied agents by intelligently switching between draft and retrieval strategies.
By integrating kinematic prediction with speculative decoding, KERV enables VLA models to achieve a 27-37% speedup in robot control tasks without sacrificing success rate.
