FocalPolicy introduces frequency-optimized chunking and locally anchored flow matching with a foresight composite objective to reduce inter-chunk discontinuities in visuomotor policies.
arXiv preprint arXiv:2510.22201 , year=
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DA-PTQ quantizes VLAs by compensating cross-space distortions and allocating mixed precision to minimize motion errors and kinematic drift in trajectories.
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FocalPolicy: Frequency-Optimized Chunking and Locally Anchored Flow Matching for Coherent Visuomotor Policy
FocalPolicy introduces frequency-optimized chunking and locally anchored flow matching with a foresight composite objective to reduce inter-chunk discontinuities in visuomotor policies.
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DA-PTQ: Drift-Aware Post-Training Quantization for Efficient Vision-Language-Action Models
DA-PTQ quantizes VLAs by compensating cross-space distortions and allocating mixed precision to minimize motion errors and kinematic drift in trajectories.