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Zelin Yao

2 accepted papers

2026

GraphSculptor: Sculpting Pre-training Core Sets for Graph Self-supervised Learning

IJCAI 2026

Graph self-supervised learning (SSL) typically relies on large-scale unlabeled datasets, heavily inflating computational costs. However, empirical evidence suggests that these datasets contain substantial redundancy—our analysis reveals that uniformly subsampling 50% of graphs retains over 96% of do

Cited by 0Scholar
2024

Gradformer: Graph Transformer with Exponential Decay

IJCAI 2024poster

Graph Transformers (GTs) have demonstrated their advantages across a wide range of tasks. However, the self-attention mechanism in GTs overlooks the graph's inductive biases, particularly biases related to structure, which are crucial for the graph tasks. Although some methods utilize positional enc…