2 citations · 4 across the 10 of their papers we have counts for
10 papers
StyleDecipher: Robust and Explainable Detection of LLM-Generated Texts with Stylistic Analysis
Siyuan Li, Aodu Wulianghai, Xi Lin +4
With the increasing integration of large language models (LLMs) into open-domain writing, detecting machine-generated text has become a critical task for ensuring content authentic…
Model-Agnostic Sentiment Distribution Stability Analysis for Robust LLM-Generated Texts Detection
Siyuan Li, Xi Lin, Guangyan Li +5
The rapid advancement of large language models (LLMs) has resulted in increasingly sophisticated AI-generated content, posing significant challenges in distinguishing LLM-generated…
Securing Distributed Network Digital Twin Systems Against Model Poisoning Attacks
Zifan Zhang, Minghong Fang, Mingzhe Chen +3
In the era of 5G and beyond, the increasing complexity of wireless networks necessitates innovative frameworks for efficient management and deployment. Digital twins (DTs), embodyi…
OpticGAI: Generative AI-aided Deep Reinforcement Learning for Optical Networks Optimization
Siyuan Li, Xi Lin, Yaju Liu +2
Deep Reinforcement Learning (DRL) is regarded as a promising tool for optical network optimization. However, the flexibility and efficiency of current DRL-based solutions for optic…
Towards Multi-Task Generative-AI Edge Services with an Attention-based Diffusion DRL Approach
Yaju Liu, Xi Lin, Siyuan Li +3
As an emerging paradigm of content creation, AI-Generated Content (AIGC) has been widely adopted by a large number of edge end users. However, the requests for generated content fr…
Multi-Agent RL-Based Industrial AIGC Service Offloading over Wireless Edge Networks
Siyuan Li, Xi Lin, Hansong Xu +4
Currently, the generative model has garnered considerable attention due to its application in addressing the challenge of scarcity of abnormal samples in the industrial Internet of…
Trustworthy AI-Generative Content for Intelligent Network Service: Robustness, Security, and Fairness
Siyuan Li, Xi Lin, Yaju Liu +2
AI-generated content (AIGC) models, represented by large language models (LLM), have revolutionized content creation. High-speed next-generation communication technology is an idea…
Spikewhisper: Temporal Spike Backdoor Attacks on Federated Neuromorphic Learning over Low-power Devices
Hanqing Fu, Gaolei Li, Jun Wu +4
Federated neuromorphic learning (FedNL) leverages event-driven spiking neural networks and federated learning frameworks to effectively execute intelligent analysis tasks over amou…
What Makes Good Collaborative Views? Contrastive Mutual Information Maximization for Multi-Agent Perception
Wanfang Su, Lixing Chen, Yang Bai +4
Multi-agent perception (MAP) allows autonomous systems to understand complex environments by interpreting data from multiple sources. This paper investigates intermediate collabora…
Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning
Kangkang Sun, Xiaojin Zhang, Xi Lin +3
Federated Learning (FL) is a novel privacy-protection distributed machine learning paradigm that guarantees user privacy and prevents the risk of data leakage due to the advantage…