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Cover image for VLA^2: Empowering Vision-Language-Action Models with an Agentic Framework forUnseen Concept Manipulation
Paperium
Paperium

Posted on • Originally published at paperium.net

VLA^2: Empowering Vision-Language-Action Models with an Agentic Framework forUnseen Concept Manipulation

Robots That Learn New Objects on the Fly – Meet VLA²

What if your robot could pick up a brand‑new gadget it has never seen before? Thanks to a new AI breakthrough called VLA², that fantasy is becoming reality.
Researchers gave a robot an “agentic” brain that lets it quickly search the web for pictures and descriptions of an unknown item, then use that knowledge to grab it safely.
It’s like a chef who, when handed an exotic fruit, instantly looks up a recipe and knows exactly how to slice it.

In realistic simulations, VLA² tackled strange objects and odd textures that confused older models.
The result? A stunning 44% jump in success on the toughest tasks and an overall 20% boost across the board, all without losing performance on familiar jobs.

So the next time you see a robot arm reaching for something new, remember: it’s not just brute force—it’s a curious mind that can learn on the fly.
The future of smart helpers is already here.

Read article comprehensive review in Paperium.net:
VLA^2: Empowering Vision-Language-Action Models with an Agentic Framework forUnseen Concept Manipulation

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