arXiv Artificial Intelligence

Screw Attention: Rigid-Body Algebra Inside a Transformer

Screw Attention: Rigid-Body Algebra Inside a Transformer

Quick summary

arXiv:2610.00904v1 Announce Type: cross Abstract: Learned manipulation policies rediscover from data the spatial relations that rigid-body mechanics supplies in closed form. This costs data, and it leaves the policies fragile to geometric changes in the scene. We present Screw Attention, a transformer layer in which the relation between two bodies is a spatial transform rather than a graph edge. Every token is a body with a pose. Each pair of tokens carries the relative pose and, for robot joints, the joint screw. Messages are transported along this relation into the receiver's frame, while th

Key takeaways

  • arXiv:2610.00904v1 Announce Type: cross Abstract: Learned manipulation policies rediscover from data the spatial relations that rigid-body mechanics supplies in closed form.
  • This costs data, and it leaves the policies fragile to geometric changes in the scene.
  • We present Screw Attention, a transformer layer in which the relation between two bodies is a spatial transform rather than a graph edge.

Why it matters

“Screw Attention: Rigid-Body Algebra Inside a Transformer” illustrates how changes in the AI ecosystem can affect products, workflows and user expectations together. Its lasting significance depends on measurable adoption, cost and safety outcomes.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗