arXiv Computer Vision October 5, 2026 By Jin Hyun, Jung Gyu Min, Gyuhyun Jung, Youngjoo Lee

CHASE-VLA: Post-Training Quantization Framework for Vision-Language-Action Models with Chunk-Aware Scale Estimation

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arXiv Machine Learning

Aug 10

{\Omega}-QVLA: Robust Quantization for Vision-Language-Action Models via Composite Rotation and Per-step Scaling

arXiv:2605. 28803v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models unify perception, reasoning, and control within a single policy, yet their multi-billion-parameter backbones and diffusion-based action heads make on-device deployment prohibitively expensive.

By Xinyu Wang, Mingze Li, Sicheng Lyu, Dongxiu Liu, Kaicheng Yang, Ziyu Zhao, Yufei Cui, Xiao-Wen Chang, Peng Lu

llms diffusion robotics efficiency multimodal

arXiv Machine Learning

Aug 12

HoloQ-VLA: Uniform W4A4 Quantization of Vision-Language-Action Models

arXiv:2605. 28803v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models unify perception, reasoning, and control in a single policy, but their multi-billion-parameter backbones and diffusion-based action heads make on-device deployment prohibitively expensive.

By Xinyu Wang, Mingze Li, Sicheng Lyu, Dongxiu Liu, Kaicheng Yang, Ziyu Zhao, Yufei Cui, Xiao-Wen Chang, Peng Lu

diffusion robotics efficiency multimodal

arXiv AI

Sep 23

FoldQuantVLA: Native Low-Bit Quantization of Vision-Language-Action Models via Consistent Folding

arXiv:2609.24433v1 Announce Type: cross Abstract: Low-bit vision-language-action inference must reduce observation-to-action latency while preserving robot behavior. We present FoldQuantVLA, a post-t...

By Hung T. Ho, Khanh D. Nguyen, Quang D. Nguyen, Thanh Q. Duong, Ngan Le, Meng Guo, Vien A. Ngo, An T. Le

robotics efficiency multimodal

Hugging Face Trending Papers

Jun 4

Let It Be Simple: One-Step Action Generation for Vision-Language-Action Models

Diffusion-based vision-language-action (VLA) models often inherit the image-generation view: actions are generated by iterative denoising. We argue that VLA action generation has a different condition-target structure: the policy is conditioned on rich observations, language, and state, but predicts only a compact, low-dimensional action chunk.

diffusion robotics efficiency multimodal safety

arXiv Machine Learning

Jun 5

Let It Be Simple: One-Step Action Generation for Vision-Language-Action Models

arXiv:2606. 05737v1 Announce Type: cross Abstract: Diffusion-based vision-language-action (VLA) models often inherit the image-generation view: actions are generated by iterative denoising.

By Yitong Chen, Shiduo Zhang, Jingjing Gong, Xipeng Qiu

diffusion robotics efficiency multimodal safety

arXiv AI

6d ago

Staircase Policy: Streaming Inference for World-Action Models with Large Action Chunks

arXiv:2609.36471v1 Announce Type: cross Abstract: World-Action Models (WAMs) improve robotic manipulation by conditioning action generation on predicted future observations, but future prediction add...

By Guoheng Sun, Chen Chen, Jin Wang, Ang Li, Teresa Lv

rag robotics efficiency

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Related stories

{\Omega}-QVLA: Robust Quantization for Vision-Language-Action Models via Composite Rotation and Per-step Scaling

HoloQ-VLA: Uniform W4A4 Quantization of Vision-Language-Action Models

FoldQuantVLA: Native Low-Bit Quantization of Vision-Language-Action Models via Consistent Folding

Let It Be Simple: One-Step Action Generation for Vision-Language-Action Models

Let It Be Simple: One-Step Action Generation for Vision-Language-Action Models

Staircase Policy: Streaming Inference for World-Action Models with Large Action Chunks