31 citations · 34 across the 6 of their papers we have counts for
6 papers
Combating Knowledge Corruption in Agent Systems: A Byzantine-Tolerant Secure Collaborative RAG Framework
Zhaoqi Wang, Daqing He, Zijian Zhang +13
While retrieval-augmented generation systems partially address the hallucination issues in large language models, it also introduces new vulnerabilities to knowledge corruption att…
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning
Zhibo Xing, Zijian Zhang, Zi'ang Zhang +3
Federated learning allows several clients to train one machine learning model jointly without sharing private data, providing privacy protection. However, traditional federated lea…
Signed Graph Representation Learning: A Survey
Zeyu Zhang, Peiyao Zhao, Xin Li +4
With the prevalence of social media, the connectedness between people has been greatly enhanced. Real-world relations between users on social media are often not limited to express…
SGA: A Graph Augmentation Method for Signed Graph Neural Networks
Zeyu Zhang, Shuyan Wan, Sijie Wang +5
Signed Graph Neural Networks (SGNNs) are vital for analyzing complex patterns in real-world signed graphs containing positive and negative links. However, three key challenges hind…
Zero-Knowledge Proof-based Verifiable Decentralized Machine Learning in Communication Network: A Comprehensive Survey
Zhibo Xing, Zijian Zhang, Ziang Zhang +8
Over recent decades, machine learning has significantly advanced network communication, enabling improved decision-making, user behavior analysis, and fault detection. Decentralize…
Enhancing Signed Graph Neural Networks through Curriculum-Based Training
Zeyu Zhang, Lu Li, Xingyu Ji +5
Signed graphs are powerful models for representing complex relations with both positive and negative connections. Recently, Signed Graph Neural Networks (SGNNs) have emerged as pot…