Paper Citation Record · LEDGER

Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation

As of 9 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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.

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.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.