Query-Side Attacks on GNN-Based KGQA: Tracing Failures from Entity Linking to Answer Generation
Score
74首次将KGQA管线按阶段隔离评估，颠覆了以往对推理环节脆弱性的假设，提供了新的失败定位视角。
实验设计严谨，使用两类扰动并在两个基准上验证，统计结论清晰，但模型覆盖范围有限。
明确指出了子图构建作为修复目标，对KGQA系统的鲁棒性改进具有直接可操作启示。
论文刚刚发布，针对的是当前GNN-KGQA领域尚未解决的故障归因问题，时效性强。
来源为arXiv预印本，作者提供了公开代码与数据集，但尚未经过同行评审。
Base 82.5 × T2 Source weight ×0.9 = 74
Curation line 70Selected
Why selected
The paper reveals a systematic failure mode masked by end-to-end metrics with rigorous experimental design, though the practical deployment value of the datasets and tasks requires further validation.
AI commentary
「This paper reminds us that end-to-end metrics can seriously mislead our judgment about weak links in complex pipelines. For those building interpretable and maintainable KGQA systems, subgraph construction is where the effort should go, rather than blindly increasing model complexity.」
Quick overview
This paper introduces a stage-isolation protocol to localize failure stages in GNN-based KGQA pipelines under adversarial perturbations. Using two answer-preserving perturbations (Compositional Restructuring and Relation Synonym Swap), evaluations on ComplexWebQuestions and WebQSP show that the GNN reasoning stage retains near-baseline accuracy when the subgraph is intact, while subgraph construction accounts for over 99% of end-to-end collapse. Even when the gold answer is present in 74% of retrieved subgraphs, subgraph construction prevents answer reachability, revealing a fundamental distinction between answer presence and answer reachability that end-to-end metrics cannot detect, and shifting the mitigation target to subgraph construction.
- Proposes a stage-isolation protocol to attribute failures across entity linking, subgraph retrieval, GNN reasoning, and answer generation
- Two answer-preserving perturbations, Compositional Restructuring (CR) and Relation Synonym Swap (RS), target distinct stages while keeping entity seeds intact
- Experiments reveal subgraph construction as the dominant failure source, accounting for over 99% of end-to-end collapse, while GNN reasoning stays near baseline
- Gold answers are present in 74% of failed retrieved subgraphs, exposing the key difference between answer presence and answer reachability
Full text
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