Deep Learning

Orion: Enabling Self-adaptive Memory Management for On-device Online Continual Learning

Online continual learning (OCL) enables real-time adaptation to new data, making it crucial for dynamic robotic applications. However, …

Zexin Li, Nikil Dutt, Cong Liu

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

TreeDiff: AST-Guided Code Generation with Diffusion LLMs

Code generation is increasingly critical for real-world applications. Still, diffusion-based large language models continue to struggle …

Yiming Zeng, Jinghan Cao, Zexin Li, Yiming Chen, Tao Ren, Zhuochun Li, Dawei Xiang, Xidong Wu, Shangqian Gao, Tingting Yu

HyperEdit: Unlocking Instruction-based Text Editing in LLMs via Hypernetworks

Instruction-based text editing is increasingly critical for real-world applications such as code editors (e.g., Cursor), but Large …

Yiming Zeng, Jinghan Cao, Zexin Li, Wanhao Yu, Zhankai Ye, Dawei Xiang, Ting Hua, Xin Liu, Shangqian Gao, Tingting Yu

NaturalSloth: Revisiting Denial-of-Service Attacks on Large Language Models

LLM serving is limited by provider-side resources: longer generations consume more GPU time, increase latency, and reduce throughput in …

Yiming Chen, Zexin Li, Xianghu Yue, Robby T. Tan, Haizhou Li

Mixtraining: A Better Trade-Off Between Compute and Performance

Incorporating self-supervised learning (SSL) before standard supervised learning (SL) has become a widely used strategy to enhance …

Zexin Li*, Jiancheng Zhang*, Yufei Li, Yinglun Zhu, Cong Liu

PIMbot: A Self-Adaptive Attack Framework for Adversarial Manipulation of Multi-Robot Reinforcement Learning

Zexin Li, Ziliang Zhang, Hyoseung Kim, Cong Liu

RED: Adaptive Real-Time DAG Scheduling for Robotic Inference under Environmental Dynamics

Zexin Li, Tao Ren, Johnathan Liu, Xiaoxi He, Cong Liu

LeMix: Unified Scheduling for LLM Training and Inference on Multi-GPU Systems

To appear soon.

Yufei Li, Zexin Li, Yinglun Zhu, Cong Liu

Collaborative Learning in Agentic Systems: A Collective AI is Greater Than the Sum of Its Parts

Agentic AI has gained significant interest as a research paradigm focused on autonomy, self-directed learning, and long-term …

Saptarshi Nath, Christos Peridis, Eseoghene Benjamin, Xinran Liu, Soheil Kolouri, Peter Kinnell, Zexin Li, Cong Liu, Shirin Dora, Andrea Soltoggio