Zexin Li
Zexin Li
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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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DeciX: Explain Deep Learning Based Code Generation Applications
Deep learning-based code generation (DL-CG) applications have shown great potential for assisting developers in programming with …
Simin Chen
,
Zexin Li
,
Wei Yang
,
Cong Liu
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DOI
Genie: Smart ROS-based Caching for Connected Autonomous Robots
To appear soon.
Zexin Li
,
Soroush Bateni
,
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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DOI
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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DOI
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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DOI
MIMONet: Multi-Input Multi-Output On-Device Deep Learning
Future intelligent robots are expected to process multiple inputs simultaneously (such as image and audio data) and generate multiple …
Zexin Li
,
Xiaoxi He
,
Yufei Li
,
Wei Yang
,
Lothar Thiele
,
Cong Liu
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PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social Dilemmas
Recent research has demonstrated the potential of reinforcement learning (RL) in enabling effective multi-robot collaboration, …
Shahab Nikkhoo
,
Zexin Li
,
Aritra Samanta
,
Yufei Li
,
Cong Liu
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DOI
Dynamic Transformers Provide a False Sense of Efficiency
Despite much success in natural language processing (NLP), pre-trained language models typically lead to a high computational cost …
Yiming Chen
,
Simin Chen
,
Zexin Li
,
Wei Yang
,
Cong Liu
,
Robby Tan
,
Haizhou Li
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