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Paper Citation Record · LEDGER

Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2207.12355.

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

pith.paper-citation-record.v1
2207.12355 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:00:03.420302Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T13:56:37.603372Z

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 cf311233-2b4d-46f8-9454-d6f2cce79bc5 · inbound

Unveiling the Black Box: A Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agents cites this paper.

Unveiling the Black Box: A Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agents Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:56:37.607082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T13:55:36.414353Z digest=sha256:19d7a219d38ebff9f478aee21150605179e6d59ed3be1e3d43be7f931be65c62

Observation 2dd09852-185f-4694-8494-9ca2ddb2cb7a · inbound

Online Identification of IT Systems through Active Causal Learning cites this paper.

Online Identification of IT Systems through Active Causal Learning Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-05T12:00:03.420302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:00:03.420302Z digest=sha256:9c3ab97af71a9d5c901b4c0b75f50f87ba7be77fea5f42027fc1114d8a672633

Observation d47500ff-3701-4911-88dd-d0c944f43449 · inbound

Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities cites this paper.

Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation

Reference 90

Resolution
verified exact
arxiv_id, observed 2026-05-18T18:06:43.045044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T18:04:09.528381Z digest=sha256:bbd215346d7ada294b4024c34c807d18c48da409b604f9a7da4229797e933312

Observation e93d6814-e0e8-4cec-b0da-7e8553f4925d · inbound

Enhancing Cloud Network Resilience via a Robust LLM-Empowered Multi-Agent Reinforcement Learning Framework cites this paper.

Enhancing Cloud Network Resilience via a Robust LLM-Empowered Multi-Agent Reinforcement Learning Framework Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-21T16:30:22.081859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T16:28:22.036007Z digest=sha256:20c9edb81f3f8c4a96901e98d97f946fea708aab43e4d102dfc0ad3d51a63408