AI RESEARCH
A Unified Perspective for Learning Graph Representations Across Multi-Level Abstractions
arXiv CS.AI
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ArXi:2605.12685v1 Announce Type: cross Graph Self-Supervised Learning (GSSL) has emerged as a powerful paradigm for generating high-quality representations for graph-structured data. While multi-scale graph contrastive learning has received increasing attention, many existing methods still predominantly focus on a single graph abstraction level.