Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.13871.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T18:39:41.182556Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T00:32:37.658109Z
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 80a51a50-155a-4745-b468-ae2c27c94391 · inbound
PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models cites this paper.
PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T18:39:41.182556Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1086be2-abaa-4b72-95a1-601efafde30d · inbound
Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability cites this paper.
Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T00:32:37.662697Z
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.