A Living Leaderboard for Graph Machine Learning
Score
56Why selected
进入全量动态池，后续可由人工或模型复核精选价值。
AI commentary
「来自 arXiv AI/CL/LG（论文） 的这条信息指向研究方向和技术路线变化，适合用于判断近期 AI 圈的真实动向。」
Quick overview
Graph machine learning benchmarking results are scattered across papers that use quite different sets of datasets and baseline methods, making it difficult to tell whether a reported gain reflects architectural progress…
- Graph machine learning benchmarking results are scattered across papers that use quite different sets of datasets and baseline methods, making it difficult to tell whether a reported gain reflects architectural progress…
- We introduce a living, graph-learning-specific leaderboard that organizes reported results by dataset, putting new results into context.
- As of 15 October 2026 our LLM-based extraction pipeline extracted 27,723 eligible results across 111 datasets from 885 peer-reviewed papers.
Full text
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