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Di Jin

ICML 2026×7数据与预训练对齐与偏好多模态

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核心/参与20

方向广度6

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0 一作 · 7 篇 · ICML 2026

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2026 顶会论文

7

作者位次 #5/5ICML 2026Poster· Deep Learning / Graph Neural Networks

GP2F: Cross-Domain Graph Prompting with Adaptive Fusion of Pre-trained Graph Neural Networks

Dongxiao He · Wenxuan Sun · Yongqi Huang · Jitao Zhao · Di Jin

数据与预训练OpenReview

作者位次 #5/5ICML 2026Poster· Deep Learning / Graph Neural Networks

Bridging Structure and Semantics: Uncertainty-Modulated Dual-Path Diffusion for Robust Text-Attributed Graph Learning

Zhizhi Yu · Jiachen Liu · Qingyu Li · Dongxiao He · Di Jin

作者位次 #4/9ICML 2026Poster· Deep Learning / Graph Neural Networks

Rethinking Graph Transformers as Graph Signal Denoisers: The Role of Block-Diagonal Priors

Jiaming Zhuo · Ziyi Ma · Kun Fu · Di Jin · Chuan Wang · Zhen Wang · Xiaochun Cao · Huazhu Fu · Liang Yang

作者位次 #6/10ICML 2026Poster· Deep Learning / Graph Neural Networks

On the Spectral Unreachability of Brain Graph Learning

Jiaming Zhuo · Shuai Zhai · Ziyi Ma · Kun Fu · Chuan Wang · Di Jin · Zhen Wang · Xiaochun Cao · Huazhu Fu · Liang Yang

作者位次 #4/5ICML 2026Poster· Deep Learning / Graph Neural Networks

Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing

Lianze Shan · Ningchong Wang · Jitao Zhao · Di Jin · Dongxiao He

作者位次 #4/4ICML 2026Poster

A Graph Foundation Model with Cross-Modal Alignment and Modality-Aware Expert Fusion for Multi-Modal Graphs

Dongxiao He · AnKang Yang · Jitao Zhao · Di Jin

对齐与偏好多模态OpenReview

作者位次 #5/8ICML 2026Poster· Deep Learning / Graph Neural Networks

Brain Networks Should Be Learned, Not Constructed

Liang Yang · Shuai Zhai · Ziyi Ma · Jiaming Zhuo · Di Jin · Chuan Wang · Zhen Wang · Xiaochun Cao

常见合作者

DHDongxiao He×4 JZJitao Zhao×3 JZJiaming Zhuo×3 ZMZiyi Ma×3 CWChuan Wang×3 ZWZhen Wang×3 XCXiaochun Cao×3 LYLiang Yang×3 KFKun Fu×2 HFHuazhu Fu×2 SZShuai Zhai×2 WSWenxuan Sun