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Paper Citation Record · LEDGER

Adversarial Examples in Deep Learning: Characterization and Divergence

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1807.00051.

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

pith.paper-citation-record.v1
1807.00051 v3

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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:17:37.587552Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T10:28:45.042207Z

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 fdfcf61d-5305-49a1-8152-31ebf50c96e5 · inbound

Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks cites this paper.

Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks Adversarial Examples in Deep Learning: Characterization and Divergence

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-14T12:17:37.587552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:17:37.587552Z digest=sha256:9001c54345241287d1ba3d3b89bce17066031eb8443bf3ce5cb96d8e0b4d5189

Observation 3bbed3aa-c276-41e6-8714-daa0cee9e41c · inbound

Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness cites this paper.

Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness Adversarial Examples in Deep Learning: Characterization and Divergence

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-14T10:28:45.047429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T10:28:44.007552Z digest=sha256:9d01d79647ee4d57a754e0219b6c016d01272e6de3cd2eba589cf75e67cd41c2