3 papers
cs.LG2026
FED-FSTQ: Fisher-Guided Token Quantization for Communication-Efficient Federated Fine-Tuning of LLMs on Edge Devices
Changyu Li, Shuanghong Huang, Jiashen Liu +5
Federated fine-tuning provides a practical route to adapt large language models (LLMs) on edge devices without centralizing private data. However, in mobile deployments, the traini…
cs.AI2026
PI-TTA: Physics-Informed Source-Free Test-Time Adaptation for Robust Human Activity Recognition on Mobile Devices
Changyu Li, Lu Wang, Ming Lei +4
Source-free test-time adaptation (TTA) is appealing for mobile and wearable sensing because it enables on-device personalization from unlabeled test streams without centralizing pr…
cs.CV2026
Wi-Spike: A Low-power WiFi Human Multi-action Recognition Model with Spiking Neural Networks
Nengbo Zhang, Yao Ying, Lu Wang +3
WiFi-based human action recognition (HAR) has gained significant attention due to its non-intrusive and privacy-preserving nature. However, most existing WiFi sensing models predom…