2 citations · 2 across the 8 of their papers we have counts for
7 papers · 1 filter
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…
TIC-GRPO: Provable and Efficient Optimization for Reinforcement Learning from Human Feedback
Lei Pang, Jun Luo, Ruinan Jin
Group Relative Policy Optimization (GRPO), recently introduced by DeepSeek, is a critic-free reinforcement learning algorithm for fine-tuning large language models. GRPO replaces t…
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…
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…
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…
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…