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Paper Citation Record · LEDGER

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2210.07321.

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

pith.paper-citation-record.v1
2210.07321 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:17:54.515904Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T03:27:26.908018Z

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 ff22b768-fd98-440e-af57-1e8f6af80ad9 · inbound

Test Security in Remote Testing Age: Perspectives from Process Data Analytics and AI cites this paper.

Test Security in Remote Testing Age: Perspectives from Process Data Analytics and AI Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T16:17:54.515904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:17:54.515904Z digest=sha256:7483b8d7d89013956ab3c21702fdea9ffbec99272601e757e7735ca11eb095b4

Observation c065ac04-ccde-424e-82d6-ff65e531240e · inbound

TransitGPT: A Generative AI-based framework for interacting with GTFS data using Large Language Models cites this paper.

TransitGPT: A Generative AI-based framework for interacting with GTFS data using Large Language Models Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-11T20:45:05.277185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:45:05.277185Z digest=sha256:50860d5c0c2e715b0858b2a39d9e565225d98c8c1ce6dc8aa0450a056d46ddb3

Observation 4413a64b-0ac7-4116-b9af-8c31cf4aea9d · inbound

BiMarker: Enhancing Text Watermark Detection for Large Language Models with Bipolar Watermarks cites this paper.

BiMarker: Enhancing Text Watermark Detection for Large Language Models with Bipolar Watermarks Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T17:36:52.760844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:36:52.760844Z digest=sha256:7254854b48929652ccd261526361b12e9bf1d6c44096c1d681d47c80a8ae852e

Observation 020ac8eb-6b61-4b45-91d5-5e3b3b70ca32 · inbound

ExaGPT: Example-Based Machine-Generated Text Detection for Human Interpretability cites this paper.

ExaGPT: Example-Based Machine-Generated Text Detection for Human Interpretability Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-23T03:27:26.910252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-23T03:27:02.516990Z digest=sha256:5506af6407f543b326681fa205207c42af4b452284dd68eb1cd7a61b2864958f

Observation 13be6ca3-a642-468c-8747-d5cd95040fd3 · inbound

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques cites this paper.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

Reference 191

Resolution
unresolved
no resolver link, observed 2026-08-06T16:24:30.538776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:24:30.538776Z digest=sha256:6af8779bb0980d49b4025dbd33938c8791798611e742d8b56a2799881167da43