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Paper Citation Record · LEDGER

A Multiagent CyberBattleSim for RL Cyber Operation Agents

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2304.11052.

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

pith.paper-citation-record.v1
2304.11052 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:52:20.657144Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:10:46.533577Z

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 1e67c4dc-9d8d-46cc-9bf5-e581d76e1fad · inbound

Optimal Security Response to Network Intrusions in IT Systems cites this paper.

Optimal Security Response to Network Intrusions in IT Systems A Multiagent CyberBattleSim for RL Cyber Operation Agents

Reference 270

Resolution
unresolved
no resolver link, observed 2026-08-09T11:52:20.657144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:52:20.657144Z digest=sha256:e88be21363c246026441f623ef3f30d2e876b4cc1eb4d329303e8d62a510e6e0

Observation da40eb9e-d858-4e54-b83a-b4d83f951e84 · inbound

Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications cites this paper.

Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications A Multiagent CyberBattleSim for RL Cyber Operation Agents

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:10:46.628329Z

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=2026-08-07T14:10:39.455948Z digest=sha256:d099bf05752b74e3992b5fdda6a4fe97c0166504faae07bef4fc04438f06c124