dailyai.report

A new research paper introduces multi-semantic basis learning to solve cross-domain generalization in Graph Foundation Models. Current GFMs fail when nodes possess multiple labels, treating them as single-class entities. This approach replaces single-vector representations with a multi-basis framework. It allows practitioners to deploy graph models across diverse domains without retraining for every label set.