1 citations · 1 across the 14 of their papers we have counts for
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One Policy, Many Styles: Where to Aggregate Preferences for Steerable Humanoid Control?
Ziqian Huang, Yuzhuo Chen, Shimin Zhang +3
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. Pref…
Beyond Imitation: Self-Improving Robot Policies via Off-Policy Q-Planning
Varun Giridhar, Anant Khandelwal, Jeremy A. Collins +2
Behaviour Cloning (BC) has driven remarkable progress in robot manipulation, yet it is fundamentally limited by its inability to self-improve: a policy that fails cannot learn from…
FuncBridge: Towards Functional Tool-Use Generalization via Keypoint Trajectory Reasoning
Chuhao Zhou, Liquan Wang, Shuxin Cao +5
While humans readily repurpose a book, a stone, or a shoe to drive a nail, robots trained on specific tools fail to transfer the same function to novel ones -- a gap we formalize a…
Hierarchical Policy Learning via Spectral Decomposition
Shuxin Cao, Liquan Wang, Walker Byrnes +3
In this paper, we identify a semantic decomposition in robot action sequences, separating task-level motion intent from execution-level refinements. By analyzing actions in the spe…
MosaicMem: Hybrid Spatial Memory for Controllable Video World Models
Wei Yu, Runjia Qian, Yumeng Li +8
Video diffusion models are moving beyond short, plausible clips toward world simulators that must remain consistent under camera motion, revisits, and intervention. Yet spatial mem…