8 papers
TetraRL: A Self-Adaptive Runtime for On-Device Deep Reinforcement Learning Systems
Zexin Li, Soheil Shirvani, Cong Liu
Autonomous robotic systems, including autonomous vehicles, drones, and mobile robots, increasingly rely on on-device Deep Reinforcement Learning (DRL) to adapt to dynamic environme…
Orion: Enabling Self-adaptive Memory Management for On-device Online Continual Learning
Zexin Li, Nikil Dutt, Cong Liu
Online continual learning (OCL) enables real-time adaptation to new data, making it crucial for dynamic robotic applications. However, its practical deployment is hindered by memor…
RED: Adaptive Real-Time DAG Scheduling for Robotic Inference under Environmental Dynamics
Zexin Li, Tao Ren, Johnathan Liu +2
Robots deployed in dynamic environments must contend with environment-driven changes that reshape computation at runtime: new tasks may appear, precedence relations can shift, and…
PIMbot: A Self-Adaptive Attack Framework for Adversarial Manipulation of Multi-Robot Reinforcement Learning
Zexin Li, Ziliang Zhang, Hyoseung Kim +1
Recent research has demonstrated the potential of reinforcement learning in effective multi-robot collaboration, particularly in social dilemmas where robots face a trade-off betwe…
LeMix: Unified Scheduling for LLM Training and Inference on Multi-GPU Systems
Yufei Li, Zexin Li, Yinglun Zhu +1
Modern deployment of large language models (LLMs) frequently involves both inference serving and continuous retraining to stay aligned with evolving data and user feedback. Common…
Mixtraining: A Better Trade-Off Between Compute and Performance
Zexin Li, Jiancheng Zhang, Yufei Li +2
Incorporating self-supervised learning (SSL) before standard supervised learning (SL) has become a widely used strategy to enhance model performance, particularly in data-limited s…
Transferable Adversarial Attacks against ASR
Xiaoxue Gao, Zexin Li, Yiming Chen +2
Given the extensive research and real-world applications of automatic speech recognition (ASR), ensuring the robustness of ASR models against minor input perturbations becomes a cr…
Genie: Smart ROS-based Caching for Connected Autonomous Robots
Zexin Li, Soroush Bateni, Cong Liu
Despite the promising future of autonomous robots, several key issues currently remain that can lead to compromised performance and safety. One such issue is latency, where we find…