Author

Ze-Min Liu

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#artificial intelligence Preprint Sep 2026

TTGBench: Benchmarking Topological Evolution and Semantic Drift in Text-attributed Temporal Graphs

A comprehensive evaluation of 17 state-of-the-art methods across Temporal Graph Neural Networks (TGNNs) and Large Language Model (LLM)-based paradigms reveals a clear capability divide between the two paradigms: TGNN-based methods excel at structural prediction but fail at semantic tracking, whereas LLM-based predictor...

Longfei Ma, Ze-Min Liu, Fei Wu · 0 citations

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. · Proceedings of the Thirty-Fi... · 0 citations