Paper Citation Record · LEDGER

PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.04435.

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

pith.paper-citation-record.v1
2402.04435 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:12:37.058184Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T21:55:05.721344Z

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 dc50a114-c6c7-466b-90a0-673c215eb9e4 · 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 PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T18:12:37.058184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d122ad7-ad2f-403f-819f-f533d34dd202 · 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 PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T15:39:55.475529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f54e476d-69bc-46a1-b338-04c0f502e195 · 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? PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:29:23.846230Z

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 6b7bc0f9-1162-4534-a1b0-b649fe0b4a64 · 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? PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:55:05.722830Z

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.