activity
20242026
most citedLEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks

2 citations · 2 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV2026

SIDeR: Semantic Identity Decoupling for Unrestricted Face Privacy

Zhuosen Bao, Xia Du, Zheng Lin +8

With the deep integration of facial recognition into online banking, identity verification, and other networked services, achieving effective decoupling of identity information fro…

cs.LG2025

LLM-Driven Stationarity-Aware Expert Demonstrations for Multi-Agent Reinforcement Learning in Mobile Systems

Tianyang Duan, Zongyuan Zhang, Zheng Lin +10

Multi-agent reinforcement learning (MARL) has been increasingly adopted in many real-world applications. While MARL enables decentralized deployment on resource-constrained edge de…

cs.NI2025

RRTO: A High-Performance Transparent Offloading System for Model Inference in Mobile Edge Computing

Zekai Sun, Xiuxian Guan, Zheng Lin +8

Deploying Machine Learning (ML) applications on resource-constrained mobile devices remains challenging due to limited computational resources and poor platform compatibility. Whil…

cs.CV2025

Defensive Adversarial CAPTCHA: A Semantics-Driven Framework for Natural Adversarial Example Generation

Xia Du, Xiaoyuan Liu, Jizhe Zhou +7

Traditional CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) schemes are increasingly vulnerable to automated attacks powered by deep neural net…

cs.CR2025

DP-TRAE: A Dual-Phase Merging Transferable Reversible Adversarial Example for Image Privacy Protection

Xia Du, Jiajie Zhu, Jizhe Zhou +5

In the field of digital security, Reversible Adversarial Examples (RAE) combine adversarial attacks with reversible data hiding techniques to effectively protect sensitive data and…

cs.LG2025

HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models

Zheng Lin, Yuxin Zhang, Zhe Chen +6

Recently, large language models (LLMs) have achieved remarkable breakthroughs, revolutionizing the natural language processing domain and beyond. Due to immense parameter sizes, fi…