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cs.RO2026
ELASTIC: Efficiently Learning to Adaptively Scale Test-Time Compute for Generative Control Policies
Andrew Zou Li, Gokul Swamy, Yonatan Bisk +1
Generative control policies (GCPs), such as diffusion policies and flow-based vision-language-action models, enable test-time scaling in robot control. Test-time compute can be all…
cs.RO2025
From Foresight to Forethought: VLM-In-the-Loop Policy Steering via Latent Alignment
Yilin Wu, Ran Tian, Gokul Swamy +1
While generative robot policies have demonstrated significant potential in learning complex, multimodal behaviors from demonstrations, they still exhibit diverse failures at deploy…
cs.RO2025
Your Learned Constraint is Secretly a Backward Reachable Tube
Mohamad Qadri, Gokul Swamy, Jonathan Francis +2
Inverse Constraint Learning (ICL) is the problem of inferring constraints from safe (i.e., constraint-satisfying) demonstrations. The hope is that these inferred constraints can th…