3 accepted papers
Diffusion Policy has demonstrated strong visuomotor modeling capabilities, but its high computational cost renders it impractical for real-time robotic control. Despite huge redundancy across repetitive denoising steps, existing diffusion acceleration techniques fail to generalize to Diffusion Polic…
Diffusion Policy has dominated action generation due to its strong capabilities for modeling multi-modal action distributions, but its multi-step denoising processes make it impractical for real-time visuomotor control. Existing caching-based acceleration methods typically rely on $\textit{static}$ …
Deep reinforcement learning (DRL) methods have achieved remarkable success in solving static traveling salesman problems (TSP). However, dynamic TSP (DTSP), with the random appearance of new customers over time, introduces additional complexities that challenge DRL methods by the difficulty of obtai