Hong Liu

D-Quant is proposed, a flexible KV cache quantization framework that introduces a Drift mechanism to convert entropy-coded representations of each token into fixed-size bitstreams, enabling regular memory access and parallel dequantization within attention kernels.

Selectively routed stereo evidence boosts humanoid VLA control success rates, achieving 100% grasp success even under severe occlusion.