Deep Learning

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
Deep Reinforcement Learning (DRL) is critical for autonomous systems to continuously learn and adapt in dynamic environments. However, …
Soheil Shirvani, Aritra Samanta, Zexin Li, Cong Liu
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Transferable Adversarial Attacks against ASR
Given the extensive research and real-world applications of automatic speech recognition (ASR), ensuring the robustness of ASR models …
Xiaoxue Gao, Zexin Li, Yiming Chen, Cong Liu, Haizhou Li
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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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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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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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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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