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Li-Na Wei

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Conference Open access Sep 2026

Learnable Data Augmentation and Contrastive Pre-training for Temporal Link Prediction

This paper proposes a novel model, ContraTGT, which employs a dual-view graph transformer, and puts forth an innovative, learnable data augmentation method, which involves selective masking of elements within dual-view sequences, thereby amplifying the potency of the contrastive learning approach.

Cang-Hong Jin, Jia-Feng Zhao, Feng Xu et al. · 0 citations

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