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Author

Cheng Yang

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#artificial intelligence Review Feb 2025

Graph Foundation Models for Recommendation: A Comprehensive Survey

This survey provides a comprehensive overview of GFM-based RS technologies by introducing a clear taxonomy of current approaches, diving into methodological details, and highlighting key challenges and future directions.

Bin Wu, Yihang Wang, Yuan-Hao Zeng et al. · 7 citations
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

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