System

BOXR: Body and head motion Optimization framework for eXtended Reality
The emergence of standalone Extended Reality (XR) systems has enhanced user mobility, accommodating both subtle, frequent head motions …
Ziliang Zhang, Zexin Li, Hyoseung Kim, Cong Liu
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DuoJoule: Accurate On-Device Deep Reinforcement Learning for Energy and Timeliness
Coming soon.
Soheil Shirvani, Aritra Samanta, Zexin Li, Cong Liu
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RT-LM: Uncertainty-Aware Resource Management for Real-Time On-Device Language Models
Recent advancements in language models~(LMs) have gained substantial attentions on their capability to generate human-like responses. …
Yufei Li, Zexin Li, Wei Yang, Cong Liu
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R^3: On-device Real-Time Deep Reinforcement Learning for Autonomous Robotics
Autonomous robotic systems, like autonomous vehicles and robotic search and rescue, require efficient on-device training for continuous …
Zexin Li, Aritra Samanta, Yufei Li, Andrea Soltoggio, Hyoseung Kim, Cong Liu
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RED: A Systematic Real-Time Scheduling Approach for Robotic Environmental Dynamics
Intelligent robots are designed to effectively navigate dynamic and unpredictable environments laden with moving mechanical elements …
Zexin Li, Tao Ren, Xiaoxi He, Cong Liu
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Efficient algorithms for task mapping on heterogeneous CPU/GPU platforms for fast completion time
In GPU-based embedded systems, the problem of computation and data mapping for multiple applications while minimizing the completion …
Zexin Li, Yuqun Zhang*, Ao Ding, Husheng Zhou, Cong Liu
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