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Paper Citation Record · LEDGER

Linguistic-style-aware Neural Networks for Fake News Detection

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2301.02792.

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

pith.paper-citation-record.v1
2301.02792 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:58:25.670299Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T06:16:15.957210Z

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 f5ce06be-714a-4b31-99ee-2641195dbe0d · inbound

GETAE: Graph information Enhanced deep neural NeTwork ensemble ArchitecturE for fake news detection cites this paper.

GETAE: Graph information Enhanced deep neural NeTwork ensemble ArchitecturE for fake news detection Linguistic-style-aware Neural Networks for Fake News Detection

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-12T00:58:26.103544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T00:58:25.670299Z digest=sha256:b611dea8b1fcefde13f73e766de83aca7810ffb13ac47951b2f5602f44e88b10

Observation b7067ad3-79e0-43c0-a16a-a43b64bba5dc · inbound

AI-Generated Content in Cross-Domain Applications: Research Trends, Challenges and Propositions cites this paper.

AI-Generated Content in Cross-Domain Applications: Research Trends, Challenges and Propositions Linguistic-style-aware Neural Networks for Fake News Detection

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-04T17:04:33.692806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:04:33.692806Z digest=sha256:989585f200933b05f4f6b3b138b25364fc2c491f155308960977405c647a2fff

Observation 3e2dc17b-eff2-4e53-a679-c9b04af4c55b · inbound

Unpacking Hateful Memes: Presupposed Context and False Claims cites this paper.

Unpacking Hateful Memes: Presupposed Context and False Claims Linguistic-style-aware Neural Networks for Fake News Detection

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-04T10:26:23.971077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:26:23.971077Z digest=sha256:42936ef250b460f11b3653c0e92fc913e16e63bdc3e85994531e653b52c92ca6