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Paper Citation Record · LEDGER

Evaluating the Adversarial Robustness for Fourier Neural Operators

As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2204.04259.

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

pith.paper-citation-record.v1
2204.04259 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 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:49:56.977960Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T10:46:02.384236Z

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 5ac94912-a26f-4654-92aa-901dde772b82 · inbound

Solver-Integrated Adversarial Attacking and Training of Neural Operators cites this paper.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Evaluating the Adversarial Robustness for Fourier Neural Operators

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-04T08:49:56.977960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:49:56.977960Z digest=sha256:30fb06576da8adb389e1b13f1d7a5500eeae889807221107f8bda59e6b62812c

Observation 68970b23-c1f7-4027-ac68-1d2ef20b329b · inbound

Beyond Uniform Sampling: Synergistic Active Learning and Input Denoising for Robust Neural Operators cites this paper.

Beyond Uniform Sampling: Synergistic Active Learning and Input Denoising for Robust Neural Operators Evaluating the Adversarial Robustness for Fourier Neural Operators

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:46:02.389972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-10T15:20:31.017699Z digest=sha256:33846a96c91f7fbb0893b762f34c48f736b5dfe39dbee11f39d5fbbf837d5692