63 citations · 183 across the 24 of their papers we have counts for
7 papers · 1 filter
ZoFia: Zero-Shot Fake News Detection with Entity-Guided Retrieval and Multi-LLM Interaction
Lvhua Wu, Xuefeng Jiang, Sheng Sun +4
The rapid spread of fake news threatens social stability and public trust, highlighting the urgent need for its effective detection. Although large language models (LLMs) show pote…
Robust Federated Learning against Noisy Clients via Masked Optimization
Xuefeng Jiang, Tian Wen, Zhiqin Yang +5
In recent years, federated learning (FL) has made significant advance in privacy-sensitive applications. However, it can be hard to ensure that FL participants provide well-annotat…
Recursive Offloading for LLM Serving in Multi-tier Networks
Zhiyuan Wu, Sheng Sun, Yuwei Wang +5
Heterogeneous device-edge-cloud computing infrastructures have become widely adopted in telecommunication operators and Wide Area Networks (WANs), offering multi-tier computational…
SVAFD: A Secure and Verifiable Co-Aggregation Protocol for Federated Distillation
Tian Wen, Sheng Sun, Yuwei Wang +4
Secure Aggregation (SA) is an indispensable component of Federated Learning (FL) that concentrates on privacy preservation while allowing for robust aggregation. However, most SA d…
FNBench: Benchmarking Robust Federated Learning against Noisy Labels
Xuefeng Jiang, Jia Li, Nannan Wu +7
Robustness to label noise within data is a significant challenge in federated learning (FL). From the data-centric perspective, the data quality of distributed datasets can not be…
Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study
Xuefeng Jiang, Lvhua Wu, Sheng Sun +5
Code vulnerability detection (CVD) is essential for addressing and preventing system security issues, playing a crucial role in ensuring software security. Previous learning-based…
Beyond Model Scale Limits: End-Edge-Cloud Federated Learning with Self-Rectified Knowledge Agglomeration
Zhiyuan Wu, Sheng Sun, Yuwei Wang +5
The rise of End-Edge-Cloud Collaboration (EECC) offers a promising paradigm for Artificial Intelligence (AI) model training across end devices, edge servers, and cloud data centers…