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20212026
most citedEfficient Heterogeneous Graph Learning via Random Projection

30 citations · 47 across the 17 of their papers we have counts for

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6 papers · 1 filter

cs.LG2026

FRACTION: Fraud Explanation Generation via Agentic Graph Context Navigation

Cecelia Soh, Jun Hu, Yuan Li +6

Graph fraud explanation generation emerges as an important task, which requires jointly leveraging graph structure and content information to produce human-readable explanations fo…

cs.LG2026★ 2 cited

NodeImport: Imbalanced Node Classification with Node Importance Assessment

Nan Chen, Zemin Liu, Bryan Hooi +3

In real-world applications, node classification on graphs often faces the challenge of class imbalance, where majority classes dominate training, resulting in biased model performa…

cs.LG2026

Multi-Label Node Classification with Label Influence Propagation

Yifei Sun, Zemin Liu, Bryan Hooi +4

Graphs are a complex and versatile data structure used across various domains, with possibly multi-label nodes playing a particularly crucial role. Examples include proteins in PPI…

cs.IR2026

Robust Multimodal Recommendation via Graph Retrieval-Enhanced Modality Completion

Yuan Li, Jun Hu, Jiaxin Jiang +2

Multimodal data plays a critical role in web-based recommendation systems, where information from diverse modalities such as vision and text enhances representation learning. Howev…

cs.AI2026

EvoClinician: A Self-Evolving Agent for Multi-Turn Medical Diagnosis via Test-Time Evolutionary Learning

Yufei He, Juncheng Liu, Zhiyuan Hu +9

Prevailing medical AI operates on an unrealistic ''one-shot'' model, diagnosing from a complete patient file. However, real-world diagnosis is an iterative inquiry where Clinicians…

cs.CL2026

Autonomous Chain-of-Thought Distillation for Graph-Based Fraud Detection

Yuan Li, Jun Hu, Bryan Hooi +2

Graph-based fraud detection on text-attributed graphs (TAGs) requires jointly modeling rich textual semantics and relational dependencies. However, existing LLM-enhanced GNN approa…