Full Professor, University of Sydney
2 papers at NeurIPS 2025
The paper proposes RAGC, a novel robust attributed graph clustering method that combines hybrid-collaborative augmentation and contrastive sample adaptive-differential awareness to obtain more discriminative representations.
This paper proposes the ACT data pipeline, which reduces human annotation costs by using MLLMs as annotators and error detectors, and provides a theoretical analysis to ensure effective downstream training.
