Author

Animesh Garg

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Preprint Oct 2026

One Policy, Many Styles: Where to Aggregate Preferences for Steerable Humanoid Control?

Modern robotic agents are increasingly expected to support steerable control, where a single policy can adjust its behavioral style at runtime under changing user preferences. Preference-conditioned reinforcement learning provides this interface, but conditioning alone does not ensure that a requested behavior change i...

Zi-Qian Huang, Yu-Zhuo Chen, Shi-Min Zhang et al. · 0 citations

Preprint Aug 2026

Beyond Imitation: Self-Improving Robot Policies via Off-Policy Q-Planning

Q-Planning is proposed, which equips a large visuomotor BC policy with a small off-policy Q-function and exploits this asymmetry to enable value-guided action selection at inference and online self-improvement that fine-tunes only the Q-function, leaving the BC weights untouched.

Varun Giridhar, Anant Khandelwal, Jeremy A. Collins et al. · 3 citations