most citedA Survey of Zero-Knowledge Proof Based Verifiable Machine Learning

3 citations · 3 across the 1 of their papers we have counts for

collaborators

7 papers

cs.CR20263 cited

A Survey of Zero-Knowledge Proof Based Verifiable Machine Learning

Zhizhi Peng, Chonghe Zhao, Taotao Wang +7

Machine learning is increasingly deployed through outsourced and cloud-based pipelines, which improve accessibility but also raise concerns about computational integrity, data priv…

cs.NI2026

Agentic Peer-to-Peer Networks: From Content Distribution to Capability and Action Sharing

Taotao Wang, Lizhao You, Jingwen Tong +2

The ongoing shift of AI models from centralized cloud APIs to local AI agents on edge devices is enabling \textit{Client-Side Autonomous Agents (CSAAs)} -- persistent personal agen…

cs.CR2026

Linking Souls to Humans: Blockchain Accounts with Credible Anonymity for Web 3.0 Decentralized Identity

Taotao Wang, Zibin Lin, Shengli Zhang +3

A decentralized identity system that can provide users with self-sovereign digital identities to facilitate complete control over their own data is paramount to Web 3.0. The accoun…

cs.IT2026

Wireless Streamlet: A Spectrum-Aware and Cognitive Consensus Protocol for Edge IoT

Taotao Wang, Long Shi, Fang Liu +2

Blockchain offers a decentralized trust framework for the Internet of Things (IoT), yet deploying consensus in spectrum-congested and dynamic wireless edge IoT networks faces funda…

cs.NI2026

An LLM-Agent-Based Framework for Age of Information Optimization in Heterogeneous Random Access Networks

Fang Liu, Erchao Zhu, Jiedan Tan +3

With the rapid expansion of the Internet of Things (IoT) and heterogeneous wireless networks, the Age of Information (AoI) has emerged as a critical metric for evaluating the perfo…

cs.CR2026

Zero-Knowledge Federated Learning: A New Trustworthy and Privacy-Preserving Distributed Learning Paradigm

Taotao Wang, Yuxin Jin, Qing Yang +3

Federated Learning (FL) has emerged as a promising paradigm in distributed machine learning, enabling collaborative model training while preserving data privacy. However, despite i…