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cs.RO2026

KeyGen: Unsupervised Keypoint based Object-Centric Representations for Category-Level Policy Generalization

Shuxin Cao, Liquan Wang, Masoud Moghani +2

Generalization in robotic manipulation requires policies to perform tasks across diverse unseen object instances that vary in shape, size, and pose. However, conventional behavior…

cs.RO2026

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation

Woo Chul Shin, Zhenyang Chen, Alfred Cueva +5

Visuomotor policies have advanced on manipulation tasks where the target object stays static during execution, but real deployments break this assumption: parts drift on conveyors…

cs.RO2026

ReSteer: Quantifying and Refining the Steerability of Multitask Robot Policies

Zhenyang Chen, Alan Tian, Liquan Wang +5

Despite strong multi-task pretraining, existing policies often exhibit poor task steerability. For example, a robot may fail to respond to a new instruction ``put the bowl in the s…

cs.RO2025

AMPLIFY: Actionless Motion Priors for Robot Learning from Videos

Jeremy A. Collins, Loránd Cheng, Kunal Aneja +3

Action-labeled data for robotics is scarce and expensive, limiting the generalization of learned policies. In contrast, vast amounts of action-free video data are readily available…

cs.RO2025

SAIL: Faster-than-Demonstration Execution of Imitation Learning Policies

Nadun Ranawaka Arachchige, Zhenyang Chen, Wonsuhk Jung +8

Offline Imitation Learning (IL) methods such as Behavior Cloning are effective at acquiring complex robotic manipulation skills. However, existing IL-trained policies are confined…