Author

Jin-Mo Lee

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#machine learning Preprint Sep 2026

NodeGround: A Node Classification Benchmark in the Graph Foundation Model Era

Can a pretrained graph model replace training and tuning a separate predictor for each dataset? Answering this requires evaluating prediction quality alongside computational cost. We present NodeGround, a node classification benchmark that puts graph foundation models (GFMs) and dataset-specific supervised learning und...

Jin-Mo Lee, Dooho Lee, Minho Jeong et al. · 0 citations

#machine learning Preprint Sep 2026

Message Passing Does More with Less for In-Context Learning on Graphs

Achieving strong performance with graph neural networks (GNNs) typically requires training and hyperparameter tuning for each dataset, incurring repeated costs and effort. Graph in-context learning (ICL) avoids this by using a single pretrained model to predict unknown node labels directly from labeled context nodes. E...

Dooho Lee, Jin-Mo Lee, Minho Jeong et al. · 0 citations