Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2503.16693.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:29:43.246771Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T08:33:14.865139Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation a3d4e200-4019-494e-8d89-8ced57857a80 · inbound
MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models cites this paper.
MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:29:43.246771Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d339b38-58cd-4a1a-bb66-536055502c1a · inbound
A Survey on Model Extraction Attacks and Defenses for Large Language Models cites this paper.
A Survey on Model Extraction Attacks and Defenses for Large Language Models ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:23:07.801022Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5c1fc816-46b2-47f6-a1e4-f4ec289b6256 · inbound
DESIGN: Encrypted GNN Inference via Server-Side Input Graph Pruning cites this paper.
DESIGN: Encrypted GNN Inference via Server-Side Input Graph Pruning ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:25:28.124679Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1cdfecf6-f830-4bb7-ba88-5339385a90db · inbound
Intellectual Property in Graph-Based Machine Learning as a Service: Attacks and Defenses cites this paper.
Intellectual Property in Graph-Based Machine Learning as a Service: Attacks and Defenses ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
Reference 108
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:39:55.729820Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e6dc2573-8724-4caa-b88f-08da776dfcbc · inbound
Can Subgraph Explanations Be Weaponized to Steal Graph Neural Networks? cites this paper.
Can Subgraph Explanations Be Weaponized to Steal Graph Neural Networks? ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T08:33:14.866919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.