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Paper Citation Record · LEDGER

Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2504.19000.

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

pith.paper-citation-record.v1
2504.19000 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:22:09.903923Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T11:17:15.653025Z

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 578df4c7-460d-4663-978a-0ccc631b7266 · inbound

On Inverse Problems, Parameter Estimation, and Domain Generalization cites this paper.

On Inverse Problems, Parameter Estimation, and Domain Generalization Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:17:15.654760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T11:13:17.446203Z digest=sha256:ac422eb69e7ee3739064fb9f7b74dee9de73677ccfe64b3d8efac7d0279f95b9

Observation b5cfc29a-9868-44b5-9c0b-b4a5d40b347d · inbound

Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses cites this paper.

Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T22:22:09.903923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:22:09.903923Z digest=sha256:408632922c272c875882da5d7d735a8b1e5e5ed9f6145f2be0720b912a4661ae