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Paper Citation Record · LEDGER

Adversarial Examples in Modern Machine Learning: A Review

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1911.05268.

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

pith.paper-citation-record.v1
1911.05268 v2

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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:54:11.594890Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T04:54:11.812992Z

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 225abb94-ee29-47b8-bfb3-d4c1230f68d2 · inbound

Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases cites this paper.

Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases Adversarial Examples in Modern Machine Learning: A Review

Reference 62

Resolution
verified exact
local_arxiv, observed 2026-08-11T04:54:11.820000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-11T04:54:11.594890Z digest=sha256:a5be900721747596c14e332eed0d95ba3c905d3e06e551e85ff3f39e8bf046ee

Observation cb6036f1-f8e2-4506-86b4-dab38923e619 · inbound

Evaluation of Adversarial Robustness in Arabic Language Models cites this paper.

Evaluation of Adversarial Robustness in Arabic Language Models Adversarial Examples in Modern Machine Learning: A Review

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-01T01:26:14.605381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T01:26:14.605381Z digest=sha256:56d8b94644e1bbfced7d1bd19ac04cf49d5da9cd05b45deec3305256c8eb0bd1