Vision-language-action models are typically built on a simple premise: perception is first compressed by visual encoders, and action reasoning begins only afterwards. Yet manipulation often hinges on
NEO-VLA eliminates fixed visual encoders to let action policies access evolving visual representations across network depths, improving manipulation robustness.
Vision-language-action models are typically built on a simple premise: perception is first compressed by visual encoders, and action reasoning begins only afterwards. Yet manipulation often hinges on precisely the visual signals most vulnerable to this abstraction, e.g., local geometry, boundaries, depth, and subtle state changes. This raises a fundamental question: should action policies inherit a fixed visual endpoint, or directly access evolving visual computation? We introduce NEO-VLA, a structurally encoder-free vision-language-action framework. Images are tokenized by lightweight patch convolutional layers and evolve jointly with language throughout the backbone, allowing a…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
From Pixels to Actions - Towards Native Vision-Language-Action Policies was first seen on Hugging Face · Daily papers on Nov 5, 2026. Since then it has appeared in 15 checks on 2 different days. Its best position was #2 of 30, reached on Nov 5, 15:28 UTC. It dropped off the list after Nov 6, 09:28 UTC.
Position on Hugging Face · Daily papers at every check (lower is better).
Best rank per day (UTC).
Platform metric as reported by Hugging Face.
Archived daily, weekly and monthly lists that include this entry.
Not at the moment. It was last on the list on Nov 6, 09:28 UTC, after 2 days of trending.
#2 on Hugging Face · Daily papers, on Nov 5, 15:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 5, 2026 and has been on the list on 2 days (15 checks) since.