Author

Shi-Rui Pan

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#machine learning Preprint Oct 2026

Is Real-World Training Data Necessary for Generalist Graph Anomaly Detection?

Generalist graph anomaly detection (GAD) aims to build a foundation model that detects anomalies on arbitrary unseen graphs without retraining or fine-tuning. Sufficient data are essential for foundation model training, yet generalist GAD still faces a data shortage, as real-world anomalous graphs are scarce and costly...

Yu-Jing Liu, Yi-Xin Liu, Yue Tan et al. · 0 citations

Preprint Aug 2026

PaSta: Noisy Node Classification with Partial Label Learning

This paper proposes a novel Partial label-based Self-training framework (PaSta) that leverages partial label learning technique to overcome the limitations of existing methods and designs a partial label-based classification model with two well-crafted loss functions to guide the model learning at both label and repres...

Yu-Jing Liu, Yi-Xin Liu, Yu Zheng et al. · 0 citations