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Paper Citation Record · LEDGER

DynaMarks: Defending Against Deep Learning Model Extraction Using Dynamic Watermarking

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2207.13321.

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

pith.paper-citation-record.v1
2207.13321 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 2026-08-05T18:12:36.532173Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T16:58:41.198048Z

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 40670c1c-329b-4802-9b1f-d11379400cad · 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 DynaMarks: Defending Against Deep Learning Model Extraction Using Dynamic Watermarking

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-05T18:12:36.532173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:12:36.532173Z digest=sha256:81249faf02f4a949a700e407e2af4931abba16f127a652e83a7fb6cc406e6310

Observation 4457e9af-7ef7-4b42-b2d7-d82a589a2e43 · inbound

LymphNode: A Plug-and-Play Access Control Method for Deep Neural Networks cites this paper.

LymphNode: A Plug-and-Play Access Control Method for Deep Neural Networks DynaMarks: Defending Against Deep Learning Model Extraction Using Dynamic Watermarking

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-20T16:58:41.200533Z

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=2026-05-20T16:58:04.893296Z digest=sha256:e904b6f5470eb7df56bab42cc4812b238d3200d3e093fe32318f549754c12d42