Author

Yujie Xing

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#machine learning Review Feb 2026

Bridging Academia and Industry: A Comprehensive Benchmark for Attributed Graph Clustering

PyAGC is presented, a comprehensive, production-ready benchmark and library designed to stress-test AGC methods across diverse scales and structural properties and advocates for a holistic evaluation protocol that mandates unsupervised structural metrics and efficiency profiling alongside traditional supervised metrics...

Yunhui Liu, Pengyu Qiu, Yu-Jie Xing et al. · arXiv.org · 5 citations

#artificial intelligence Preprint Oct 2026

Towards One-for-All Foundation Model for Attributed Graph Clustering

Attributed graph clustering aims to discover node groups by jointly exploiting node attributes and graph topology, yet its unsupervised nature makes model selection and adaptation inherently difficult. Existing methods typically train and tune a separate model for each input graph, leading to costly and fragile pipelin...

Yunhui Liu, Xu-Dong Jin, Kang Zhang et al. · 1 citation

Preprint Aug 2026

GABench: A Comprehensive Benchmark for Evaluating LLM Agents on Graph Analysis Tasks

GABench is introduced, a comprehensive benchmark for agentic graph analysis that covers four graph analysis task categories: graph retrieval, graph theory, graph machine learning, and graph open-ended question answering and provides practical insights into the development and evaluation of LLM agents for graph analysis...

Jiarui Tan, Zhong-Jian Zhang, Yabo Guo et al. · 2 citations