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Paper Citation Record · LEDGER

Safety in Graph Machine Learning: Threats and Safeguards

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.11034.

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

pith.paper-citation-record.v1
2405.11034 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:21:56.690843Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T18:12:40.188255Z

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 3eb2e033-8658-4f4f-b5c3-4e39c2cb5be0 · inbound

Generative Risk Minimization for Out-of-Distribution Generalization on Graphs cites this paper.

Generative Risk Minimization for Out-of-Distribution Generalization on Graphs Safety in Graph Machine Learning: Threats and Safeguards

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-08T11:21:56.690843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:21:56.690843Z digest=sha256:297e57fe206a6ff21a850b67cacd945fd7616ad2c6c7e2e5e41204dbf9e9e408

Observation a529850a-7579-4cc0-90be-583fd4ba637b · 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 Safety in Graph Machine Learning: Threats and Safeguards

Reference 211

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T18:12:40.194226Z

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.

source=pdf_text observed=2026-08-05T18:12:37.934513Z digest=sha256:3ab72835c55ccae073c7a19880de5c44ccf5ea6fb5999e4e1ecbdcf0368d34c5