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Paper Citation Record · LEDGER

Prompted Contextual Vectors for Spear-Phishing Detection

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.08309.

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

pith.paper-citation-record.v1
2402.08309 v3

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 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:36:40.553816Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T12:43:16.996294Z

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 2fd20f34-b881-4f87-8f7a-33b17675b836 · inbound

Phishing Awareness via Game-Based Learning cites this paper.

Phishing Awareness via Game-Based Learning Prompted Contextual Vectors for Spear-Phishing Detection

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T17:36:40.553816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:36:40.553816Z digest=sha256:2b6af13a27be99f3ce93adc9ec004508b273aee3657fad79476615f239de6e7f

Observation 318694d3-a46e-4333-916b-47e8d99d27e7 · inbound

Enhancing Phishing Email Identification with Large Language Models cites this paper.

Enhancing Phishing Email Identification with Large Language Models Prompted Contextual Vectors for Spear-Phishing Detection

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-08T21:38:52.578308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:38:52.578308Z digest=sha256:4e47917ec96c5281dbca2bfa26784a8e44bde13d8da646af5bf08e74b0f7d02d

Observation a08bb12d-c878-4db1-ad1b-9b5c2ab6ad91 · inbound

PiMRef: Detecting and Explaining Ever-evolving Spear Phishing Emails with Knowledge Base Invariants cites this paper.

PiMRef: Detecting and Explaining Ever-evolving Spear Phishing Emails with Knowledge Base Invariants Prompted Contextual Vectors for Spear-Phishing Detection

Reference 113

Resolution
unresolved
no resolver link, observed 2026-08-06T15:38:31.768181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:38:31.768181Z digest=sha256:5f83d5a4a424c30b0995af796a7f29000e776d6ee27c2ea440cb03207a645276

Observation 2219a772-585a-4c9b-b9bc-fc7af291fa1a · inbound

Can We End the Cat-and-Mouse Game? Simulating Self-Evolving Phishing Attacks with LLMs and Genetic Algorithms cites this paper.

Can We End the Cat-and-Mouse Game? Simulating Self-Evolving Phishing Attacks with LLMs and Genetic Algorithms Prompted Contextual Vectors for Spear-Phishing Detection

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:43:16.999771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T12:43:16.830435Z digest=sha256:fa4cca8bd9b982d10074a9a50334b216f9a189f5670d7f6fabab3e41a83f36e3

Observation c0f042ea-4b95-4cb4-b159-7a30a45bf457 · inbound

Large Language Models for Security Operations Centers: A Comprehensive Survey cites this paper.

Large Language Models for Security Operations Centers: A Comprehensive Survey Prompted Contextual Vectors for Spear-Phishing Detection

Reference 153

Resolution
unresolved
no resolver link, observed 2026-08-04T17:32:21.249081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:32:21.249081Z digest=sha256:2ee49db59862a6078494803d580992f0c34e2a41c8daafbfefab31c9f05df1cc