219 citations · 378 across the 62 of their papers we have counts for
7 papers · 1 filter
Frequency-Aware Continual Learning for Smart Contract Vulnerability Detection with Large Language Models
Tenghui Huang, Jiawen Kang, Dongning Liu +5
Smart contract vulnerability detection with Large Language Models (LLMs) faces three causally linked challenges. First, new vulnerability categories demand parameter-efficient adap…
Split and Aggregation Learning for Foundation Models Over Mobile Embodied AI Network (MEAN): A Comprehensive Survey
Qianzhou Chen, Siqi Sun, Minrui Xu +6
The rapid advancements in foundation models and sixth-generation (6G) wireless communication systems necessitate the development of efficient, scalable, and privacy-preserving mach…
From Digital Twins to World Models:Opportunities, Challenges, and Applications for Mobile Edge General Intelligence
Jie Zheng, Dusit Niyato, Changyuan Zhao +2
The rapid evolution toward 6G and beyond communication systems is accelerating the convergence of digital twins and world models at the network edge. Traditional digital twins prov…
Agentic Cognitive Profiling: Realigning Automated Alzheimer's Disease Detection with Clinical Construct Validity
Jiawen Kang, Kun Li, Dongrui Han +5
Automated Alzheimer's Disease (AD) screening has predominantly followed the inductive paradigm of pattern recognition, which directly maps the input signal to the outcome label. Th…
Efficient Cross-View Localization in 6G Space-Air-Ground Integrated Network
Min Hao, Yanbing Xu, Maoqiang Wu +6
Recently, visual localization has become an important supplement to improve localization reliability, and cross-view approaches can greatly enhance coverage and adaptability. Meanw…
Compact LLM Deployment and World Model Assisted Offloading in Mobile Edge Computing
Ruichen Zhang, Xiaofeng Luo, Jiayi He +3
This paper investigates compact large language model (LLM) deployment and world-model-assisted inference offloading in mobile edge computing (MEC) networks. We first propose an edg…
Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization
Jie Zheng, Ruichen Zhang, Dusit Niyato +5
Enhancing future wireless networks presents a significant challenge for networking systems due to diverse user demands and the emergence of 6G technology. While reinforcement learn…