Yanzhe Wen — accepted AI-conference papers

2026

HIAL: Towards Semantics-Aware Hypergraph Active Learning via Dual-Perspective Information Maximization

Yanheng Hou, Xunkai Li, Yanzhe Wen, Zhenjun Li, Bing Zhou, Rong-Hua Li +1

ICML 2026poster

Hypergraph Neural Networks (HNNs) model high-order interactions effectively but rely on costly node annotations, motivating Hypergraph Active Learning (HAL). However, many HAL pipelines adapt graph-based querying through clique expansion, which introduces structural bias and can cause \emph{ranking …

Cited by 0 Source ↗Scholar ↗

2026

When LLMs Encounter Open-world Graph Learning: A Fresh View on Unlabeled Data Uncertainty

Yanzhe Wen, Xunkai Li, Qi Zhang, Lei Zhu, Guang Zeng, Zhihan Zhang +2

ICML 2026poster

Recently, large language models (LLMs) have driven a systematic shift in the graph ML com- munity through the adoption of text-attributed graphs (TAGs). Although a variety of frameworks have been developed, most fail to properly ad- dress the challenge of data uncertainty in open- world environments…

Cited by 0 Source ↗Scholar ↗