[ICLR 2026] The offical Implementation of "Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model"
Explore and test a model that helps robots understand and perform tasks involving vision and language.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytime[ICLR 2026] The offical Implementation of "Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model"
X-VLA has 692 stars on GitHub. It has been forked 67 times. X-VLA is written mainly in C++. It has been in active development since 2025. X-VLA is available under the Apache-2.0 license. Its main topics are cloth-folding, florence-2, manipulation, pretrained-models.
[ICLR 2026] The offical Implementation of "Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model"
X-VLA is an open-source project. It is released under the Apache-2.0 license.
Yes. X-VLA is free and open source — you can use, modify and self-host it.
X-VLA is available under the Apache-2.0 license.
X-VLA is written mainly in C++.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/2toinf-x-vla.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.