Skip to content
Log in
Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Wei-Zhi Meng

h-index 1 View on Semantic Scholar

We have 4 of 18 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access 2026

Dropout-Tolerant Privacy-Preserving Aggregation for Federated Mobile Crowdsensing

Federated Learning (FL) has emerged as a key enabler for privacy-preserving, decentralized sensing systems, giving rise to Federated Mobile Crowdsensing (F-MCS). A well-known bottleneck in such systems is the inefficiency of synchronous training, which stalls for all participants and is susceptible to stragglers in het...

Xiao-Di Wang, Yun-Wei Dong, Wei-Zhi Meng et al. · 1 citation
Open access Oct 2026

PPT-AMA: Privacy Protection and Traceability Anonymous Mutual Authentication Protocol for Heterogeneous Vehicular Networks

Under the discrete logarithm and computational Diffie-Hellman assumption, PPT-AMA is shown to meet various security requirements, including perfect forwards secrecy and known session-specific temporary information security, highlighting the protocol’s potential for practical application.

Yong Wu, Bei Gong, Hao-Tian Zhu et al. · 0 citations
#graph neural networks Open access Oct 2026

Fed-MoSeC: A Federated Learning Framework for Cross-Modal Semantic Communication Systems in Mobile Networks

Semantic communication systems in mobile networks necessitate real-time collaborative updates of semantic encoders as a result of node mobility that induces semantic extraction drift. However, diversity within modal transmission content and heterogeneous encoder architectures, along with challenges such as imbalanced t...

Yushi Wang, Zheng-Xin Yu, Gu-Han Zheng et al. · 0 citations
Open access Jul 2026

BioZKFHE: Scalable Encrypted Biometric Identification via Verifiable Homomorphic Similarity Evaluation

BioZKFHE is presented, a framework for scalable encrypted biometric identification via verifiable homomorphic similarity evaluation that combines BGV homomorphic computation with committee-mediated proof opening/decryption and smart-contract verification of opened proof batches.

Rundong Xin, Taotao Wang, Xiaoxiao Wu et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.