Boundary Degree as a Node-level Feature for Epidemic Scenario Identification in Agent-based Cascade Simulations
arXiv 2606.29596•4c4c0cb3be8c97fc6431dfc7456228b1518059f1470cfe15d081176eb0057806
AI-governanceHGNNKesten-StigumLLM-assisted-governanceSIS-modeladversarial-MLagentic-systemsblack-box-attacksboundary-degreecommunity-detectioncontact-tracingdetector-instabilityedge-deletion-mitigationemergent-behaviorepidemic-modelinggraph-securityhard-label-attacksheterogeneous-graph-neural-networksknowledge-graphsmodel-robustnessmulti-agent-systemsprivacyquery-limited-attacks
Paper metadata
- arXiv ID
- 2606.29596
- Version
- Not specified by this published record
- Category
- Computer Science — Social and Information Networks (cs.SI)
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Evidence and limitations
- Source ID
- arxiv_cs_si
- Record identifier
- 4c4c0cb3be8c97fc6431dfc7456228b1518059f1470cfe15d081176eb0057806
- Enrichment time
- 2026-06-30T08:52:15Z
- AI-assisted enrichment
- Yes
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