Ming Hu

NebulaFL: Effective Asynchronous Federated Learning for JointCloud Computing

2024 · arXiv (Cornell University)

With advancements in AI infrastructure and Trusted Execution Environment (TEE) technology, Federated Learning as a Service (FLaaS) through JointCloud Computing (JCC) is promising to break through the resource constraints caused by heterogeneous edge devices in …

CE-FFT: Communication-Efficient Federated Fine-Tuning for Large Language Models via Quantization and In-Context Learning

2025

Although Federated Fine-Tuning (FFT) facilitates the fine-tuning of Large Language Models (LLMs) across data owners without compromising their privacy, it suffers from severe communication overheads caused by numerous parameters of LLMs even with Parameter-Efficient Fine-Tuning …

Towards Visual Discrimination and Reasoning of Real-World Physical Dynamics: Physics-Grounded Anomaly Detection

2025

Humans detect real-world object anomalies by perceiving, interacting, and reasoning based on object-conditioned physical knowledge. The long-term goal of Industrial Anomaly Detection (IAD) is to enable machines to autonomously replicate this skill. However, current IAD …