Author

Zhibo Wang

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#federated learning Oct 2026

Unlocking the Potential of Asynchronous Federated Learning in Non-IID Edge Environments

Asynchronous Federated Learning (AFL) enhances the efficiency of edge collaborative learning systems by asynchronously aggregating client updates to prevent slowdowns from slow clients. However, in non-IID scenarios, such operations magnify uneven learning among various local data, degrading global model generalization...

Xiaoyi Pang, Yajie Zhou, Zhibo Wang et al. · IEEE Transactions on Mobile... · 0 citations

Preprint Aug 2026

Inverting the Hidden: Unveiling Multimodal Privacy Leakage in Collaborative LVLM Inference

Results show that privacy-sensitive visual and textual information can be recovered even from deep-layer LVLM hidden states, exposing the privacy risks of collaborative inference.

Shuaifan Jin, Zhibo Wang, Qiyuan Wang et al. · 0 citations

Jul 2026

Attention-Free and Lightweight Token Reduction for Efficient Vision-Language Models

An attention-free and lightweight token reduction framework as a plug-and-play module for VLMs, which preserves both important and diverse tokens to produce a compact visual representation, and achieves a favorable accuracy-efficiency trade-off.

Xuanyi Hao, Zuoyuan Zhang, Zhibo Wang et al. · arXiv.org · 0 citations