Paper Citation Record · LEDGER

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence

As of 14 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2411.17585.

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

pith.paper-citation-record.v1
2411.17585 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:02:40.889516Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:03:18.519635Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T21:03:18.690332Z

Reference resolution

33 of 33 outbound references displayed

verified exact4
verified fuzzy7
unresolved20
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 01af10ca-db47-4a3d-9422-510d4794a23b · outbound

This paper cites Automated Cyber Defence: A Review.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Automated Cyber Defence: A Review

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.769760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf817c07-1578-4321-bb8b-e658c2ba2714 · outbound

This paper cites Kott et al.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Kott et al

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:02:41.471169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 892e682b-a2b9-40f3-ae95-2238592d501b · outbound

This paper cites Quantitative Measurement of Cyber Resilience: Modeling and Experimentation.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Quantitative Measurement of Cyber Resilience: Modeling and Experimentation

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-12T12:02:41.364315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 95d8713c-43bf-4122-8004-a6243170fa87 · outbound

This paper cites CybORG: A Gym for the Development of Autonomous Cyber Agents.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence CybORG: A Gym for the Development of Autonomous Cyber Agents

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.781736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb214e28-f38d-45e6-a61f-c64fd81844aa · outbound

This paper cites Bates, V.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Bates, V

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.785269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a71a4ce-bcb0-4a97-9437-6d8bfb60b7e5 · outbound

This paper cites Beyond CAGE: Investigating Generalization of Learned Autonomous Network Defense Policies.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Beyond CAGE: Investigating Generalization of Learned Autonomous Network Defense Policies

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.789669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04a436e4-309e-4d26-8610-7c0bf82aeac3 · outbound

This paper cites an unresolved cited work.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.793862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 763c1254-3fa7-49bb-b5bc-db2148bc13f0 · outbound

This paper cites Abels, D.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Abels, D

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:02:41.459774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b773dd45-7931-41f0-9316-8f811958fd54 · outbound

This paper cites Liu and X.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Liu and X

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:02:41.449551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3264163e-14d8-4c9c-afbe-97810a7b881f · outbound

This paper cites Van Moffaert, M.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Van Moffaert, M

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.805289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 256efb16-5e6c-409a-8765-76e10f4cb953 · outbound

This paper cites an unresolved cited work.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:02:41.439366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b06a6f86-f1bf-4fe4-ac8d-9bfc492824e6 · outbound

This paper cites Van Moﬀaert and A.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Van Moﬀaert and A

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:02:41.417237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 12bf7401-296a-4991-b541-9284f1fc115e · outbound

This paper cites Pareto Conditioned Networks.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Pareto Conditioned Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.819657Z

Source-reported events for the cited work

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Observation 63bef60f-fe8e-48a0-a249-9dda6b632686 · outbound

This paper cites A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.822995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bde770b-5c1d-4a85-90ab-535729f61e4a · outbound

This paper cites Skalse, L.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Skalse, L

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:02:41.406536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a7b524bd-18ef-47b5-a4da-80b45e61412f · outbound

This paper cites Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.834038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16ecd45c-50ba-44d0-a281-515f813cbec7 · outbound

This paper cites Schrittwieser et al., ‘Mastering Atari, Go, chess and shogi by planning with a learned model’, Nature, vol.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Schrittwieser et al., ‘Mastering Atari, Go, chess and shogi by planning with a learned model’, Nature, vol

Reference 17

Resolution: malformed identifier; no resolver link, observed 2026-08-12T12:02:40.838110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d7476cf-83af-4048-aa22-249218d4307a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Proximal Policy Optimization Algorithms

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.841532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94ef4ee5-0439-4c26-8dab-1d6763ecea40 · outbound

This paper cites An Optimistic Perspective on Offline Reinforcement Learning.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence An Optimistic Perspective on Offline Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.845258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation feebd25d-a516-48be-a6d5-2df793e20504 · outbound

This paper cites Decision Transformer: Reinforcement Learning via Sequence Modeling.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Decision Transformer: Reinforcement Learning via Sequence Modeling

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.849358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cba7dfe-1203-4e7b-b013-e613b43c7ed3 · outbound

This paper cites The RL/LLM Taxonomy Tree: Reviewing Synergies Between Reinforcement Learning and Large Language Models.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence The RL/LLM Taxonomy Tree: Reviewing Synergies Between Reinforcement Learning and Large Language Models

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-12T12:02:41.170445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1227aaeb-7e2e-44dc-a4bd-642ecb8ceaa4 · outbound

This paper cites Toward Diverse Text Generation with Inverse Reinforcement Learning.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Toward Diverse Text Generation with Inverse Reinforcement Learning

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-12T12:02:41.155690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 651534b6-3705-4498-89f3-30cf016bb184 · outbound

This paper cites Foley, K.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Foley, K

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.861136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11c87942-2cec-4280-8348-1e38a379147c · outbound

This paper cites Inroads into Autonomous Network Defence using Explained Reinforcement Learning.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Inroads into Autonomous Network Defence using Explained Reinforcement Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.864353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddac07b7-de97-4c5d-bf04-f3891b21a152 · outbound

This paper cites Acuto and S.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Acuto and S

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:02:41.395992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1070fc85-6b6e-411e-a42a-ad6303a5add4 · outbound

This paper cites Behaviour-Diverse Automatic Penetration Testing: A Curiosity-Driven Multi-Objective Deep Reinforcement Learning Approach.

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 7fa06854-ffcd-481b-846c-e2cf00d82606 · outbound

This paper cites an unresolved cited work.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:02:41.385788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f4021c3a-54ad-4c1d-aca4-f2b21361128e · outbound

This paper cites an unresolved cited work.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.878606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37de4480-68c5-44a0-8ce1-07f5e5704f72 · outbound

This paper cites The Fairness-Accuracy Pareto Front.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence The Fairness-Accuracy Pareto Front

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.882555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 665db456-95e9-4dce-a217-8390a05d83f6 · outbound

This paper cites You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-12T12:02:41.035913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 090b6887-ca8f-4a52-af20-a8e3c96b99a3 · outbound

This paper cites gamma": 0.99.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence gamma": 0.99

Reference 31

Resolution: metadata mismatch; raw_fallback, observed 2026-08-12T12:02:41.017502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ee2db359-9aac-4b5a-bcef-6a4019ef8d7e · outbound

This paper cites Available: https://proceedings.mlr.press/v119/xu20h.html.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Available: https://proceedings.mlr.press/v119/xu20h.html

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:02:41.427605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f51862d9-a0ab-4142-9979-4bf77223f7da · outbound

This paper cites an unresolved cited work.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence Unresolved cited work

Reference 3436

Resolution: unresolved; no resolver link, observed 2026-08-12T12:02:40.830768Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation c09de5ba-2b2f-410e-87be-7013c6316f46 · inbound

An Empirical Game-Theoretic Analysis of Autonomous Cyber-Defence Agents cites this paper.

An Empirical Game-Theoretic Analysis of Autonomous Cyber-Defence Agents Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-09T21:03:18.697595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.