Paper Citation Record · LEDGER

Adversarial Model Extraction on Graph Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1912.07721.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1912.07721 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:12:37.075878Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T21:55:05.723853Z

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 068b43ff-4ddf-45d6-99cd-233a0c9a496e · inbound

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives cites this paper.

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives Adversarial Model Extraction on Graph Neural Networks

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-05T18:12:37.075878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f858406-15de-4904-a9de-aeb614f8cc5a · 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 Adversarial Model Extraction on Graph Neural Networks

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T15:39:55.395968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4131aa6a-5bdd-4cfc-ab92-02e331d8b750 · inbound

COPYCOP: Ownership Verification for Graph Neural Networks cites this paper.

COPYCOP: Ownership Verification for Graph Neural Networks Adversarial Model Extraction on Graph Neural Networks

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:16:13.048690Z

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.

Observation 0e8148f6-2333-40d8-92bf-2e73b7bc6312 · inbound

GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It? cites this paper.

GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It? Adversarial Model Extraction on Graph Neural Networks

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:29:23.770640Z

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.

Observation 7e65741f-935a-4628-8d76-5807ff671cf7 · inbound

GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It? cites this paper.

GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It? Adversarial Model Extraction on Graph Neural Networks

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:55:05.725284Z

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.