Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Behaviour-Diverse Automatic Penetration Testing: A Curiosity-Driven Multi-Objective Deep Reinforcement Learning Approach
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2202.10630.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:02:40.871217Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T21:51:40.686722Z
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 1070fc85-6b6e-411e-a42a-ad6303a5add4 · inbound
Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence cites this paper.
Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Behaviour-Diverse Automatic Penetration Testing: A Curiosity-Driven Multi-Objective Deep Reinforcement Learning Approach
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:02:40.871217Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd38d58c-98f9-4750-bedd-c193e74201e4 · inbound
Mind the Gap: Towards Generalizable Autonomous Penetration Testing via Domain Randomization and Meta-Reinforcement Learning cites this paper.
Mind the Gap: Towards Generalizable Autonomous Penetration Testing via Domain Randomization and Meta-Reinforcement Learning Behaviour-Diverse Automatic Penetration Testing: A Curiosity-Driven Multi-Objective Deep Reinforcement Learning Approach
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T21:51:40.700168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f9f3d008-a026-4ce2-8099-b3a8898ef15b · inbound
Learning Robust Penetration Testing Policies under Partial Observability: A systematic evaluation cites this paper.
Learning Robust Penetration Testing Policies under Partial Observability: A systematic evaluation Behaviour-Diverse Automatic Penetration Testing: A Curiosity-Driven Multi-Objective Deep Reinforcement Learning Approach
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T15:17:41.144781Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.