HERALD：面向异质性感知图压缩的自适应地标蒸馏高保真样本检索

中文摘要 AI 辅助

图压缩旨在生成一个小的替代图，以保留更大原始图的下游节点分类性能。现有方法依赖于Weisfeiler-Lehman邻域聚合或基于梯度的分布匹配，两者均假设相邻节点共享相同标签，这一假设在异质性下不成立。我们提出HERALD（高保真样本检索与自适应地标蒸馏），一种无梯度的图压缩框架，将压缩流程中的节点评分和特征选择自适应地适配于图测得的异质性。HERALD通过联合Fisher可判别性和激活密度准则选择特征，在异质性图上降低聚合表示的权重，并通过原型代表性、决策边界邻近性和局部内在维度（LID）的加权组合对节点评分，其中权重由异质性比率的平滑sigmoid函数驱动。随后，通过分数排序的BFS扩展、个性化PageRank剪枝和类别再平衡将节点组装成压缩子图，所有操作在存储预算与BONSAI相同的情况下进行，从而实现直接比较。在涵盖同质性和异质性设置的八个基准数据集上的实验表明，HERALD在异质性图上匹配或超越最先进的压缩器，并在四种GNN架构下在同质性图上保持竞争力。

英文摘要

Graph condensation aims to produce a small surrogate graph that preserves the downstream node-classification performance of a much larger original graph. Existing methods rely on Weisfeiler-Lehman neighbourhood aggregation or gradient-based distribution matching, both of which assume that adjacent nodes share the same label, an assumption that breaks down under heterophily. We propose HERALD (High-fidelity Exemplar Retrieval with Adaptive Landmark Distillation), a gradient-free graph condensation framework that adapts the node scoring and feature selection in the condensation pipeline to the graph's measured heterophily. HERALD selects features via a joint Fisher-discriminability and activation-density criterion that down-weights aggregated representations on heterophilic graphs, and scores nodes by a weighted combination of prototype representativeness, decision-boundary proximity, and Local Intrinsic Dimensionality (LID), where the weights are driven by a smooth sigmoid function of the heterophily ratio. Nodes are then assembled into a condensed subgraph through score-ordered BFS expansion, Personalised PageRank pruning, and class rebalancing, all at an identical storage budget to BONSAI, enabling direct comparison. Experiments on eight benchmark datasets spanning homophilic and heterophilic settings show that HERALD matches or outperforms state-of-the-art condensers on heterophilic graphs and remains competitive on homophilic ones across four GNN architectures.

发表机构

• Indian Institute of Science Education and Research Thiruvananthapuram（印度科学教育与研究学院蒂鲁文南特普拉姆分校）

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