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Sponsored AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI

Author

Jinghao Liu

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#federated learning Nov 2026

Uncertainty-Aware Federated Categorical Dirichlet Allocation for Reliable Industrial Systems

For distributed industrial systems, federated learning (FL) can collaborate with a large number of devices for efficient modeling without sharing local data. However, the unreliability of the global model in existing FL methods poses a significant barrier to practical industrial applications. To promote the reliability...

Fang-Yu Li, Jing-Hao Liu, Xu-Qiang Chen et al. · 0 citations
#federated learning Sep 2026

FedHiPL: Federated Hierarchical Prototype Learning for Heterogeneous Non-IID Data

Federated learning (FL) collaboratively trains models across networked industrial Internet of Things (IIoT) terminals. However, statistical heterogeneity in IIoT data often hinders the performance of global models. Current FL methods typically focus on single-level representation alignment and fail to exploit gradient-...

Fangyu Li, Zhi-Cheng Chen, Jinghao Liu et al. · 0 citations
Open access Dec 2025

AI security beyond core domains: resume screening as a case study of adversarial vulnerabilities in specialized LLM applications

A benchmark for this vulnerability in LLM-based resume screening is introduced: 463 job-candidate pairs drawn from a 14-domain corpus, with the evaluated sample covering 13 domains, attacked through a taxonomy of four attack types and four injection positions.

Hong-Lin Mu, Jinghao Liu, Kai-Yang Wan et al. · 4 citations · ⚡1

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