arXiv 2610.25043 · cs.AI · 2026-10-18
VLA-Rolling: Fewer Denoising Steps, Better Control via Adaptive Action Reuse
Sicheng He, Yi Pan, Qiuting Yu, Jiaming Huang, Qi Lu, Shuyan Wu, Hongyan Feng, Xuanyu Liu and 5 more
ZJU-OmniAI
In latest · #273 Added on 2026-10-22
One-line takeaway
VLA-Rolling reuses the unexecuted action tail as the starting point for denoising, cutting steps for frozen flow-matching VLAs while often raising success.
VLA-Rolling 复用上一段未执行的动作尾巴作为去噪起点，用更少步数生成动作，冻结模型即可提速并提高成功率。
Read on arXiv PDF Hugging Face discussion Code Project page
Topics & disciplines
More on Robotics & embodied AI
- Has GPT-6-Astra Achieved Embodied Intelligence? ▲459
- In-Context Learning for Robots: Methods and Applications ▲388
- HexaShell: A Thin Harness for Exploring the Limits of VLM Agents as Robot Coding Agents ▲313
- GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives ▲310
- Ropedia W0: Scaling Loco-Manipulation World Models across Embodiments with Human Experience ▲179
About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.