Haoyue Deng — accepted AI-conference papers

2026

Discriminative Mixture-of-Experts on Graphs with Reliable Expert Fusion

Haoyue Deng, Menghui Wang, Yunlong Zhou, Ziwei Zhang, Ran Zhang, Chunming Hu +1

ICML 2026poster

Graph Mixture-of-Experts (Graph-MoE) offers a way to scale GNNs via adaptive capacity allocation, with the goal of allowing different experts to capture diverse graph patterns. Its effectiveness heavily depends on the coordination between routing decisions and expert specialization. However, through…

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2024

Uncovering the Redundancy in Graph Self-supervised Learning Models

Zhibiao Wang, Xiao Wang, Haoyue Deng, Nian Liu, Shirui Pan, Chunming Hu

NeurIPS 2024poster

Graph self-supervised learning, as a powerful pre-training paradigm for Graph Neural Networks (GNNs) without labels, has received considerable attention. We have witnessed the success of graph self-supervised learning on pre-training the parameters of GNNs, leading many not to doubt that whether the…

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