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Squeeze your embodied AI models: DyQ-VLA cuts memory footprint by 70% and speeds up inference by 40% without sacrificing performance, all by dynamically adjusting bit-widths based on real-time kinematic data.
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.
