EquiVLA is the first general framework for end-to-end SO(2)-equivariant VLA models using EquiPerceptor and EquiActor modules, reporting improved success rates on LIBERO, CALVIN, and real-robot benchmarks.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
AnyMug trains a single closed-loop visuomotor policy in simulation using observation-action canonicalization and deploys it zero-shot on a real robot for functional mug-handle grasping across poses.
citing papers explorer
-
EquiVLA: A General Framework for Rotationally Equivariant Vision-Language-Action Models
EquiVLA is the first general framework for end-to-end SO(2)-equivariant VLA models using EquiPerceptor and EquiActor modules, reporting improved success rates on LIBERO, CALVIN, and real-robot benchmarks.
-
Pose-Agnostic Robotic Functional Grasping via Observation-Action Canonicalization
AnyMug trains a single closed-loop visuomotor policy in simulation using observation-action canonicalization and deploys it zero-shot on a real robot for functional mug-handle grasping across poses.