Paper Citation Record · LEDGER

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations

As of 9 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2607.28826.

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

pith.paper-citation-record.v1
2607.28826 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T01:39:55.628235Z

measured 28 of 28 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

verified exact4
verified fuzzy0
unresolved22
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7d121184-8e86-4dbe-ab53-fc5888b650df · outbound

This paper cites In: 12th International Conference on Learning Representations, ICLR 2024, May 7, 2024 - May 11, 2024.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations In: 12th International Conference on Learning Representations, ICLR 2024, May 7, 2024 - May 11, 2024

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:52.221635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d39cebb1-e7fc-40a5-aee5-3df95b617b5f · outbound

This paper cites HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs)

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:52.279475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d71b292-118d-475d-8e7c-fc023c6edb0a · outbound

This paper cites CybORG: An Autonomous Cyber Operations Research Gym.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations CybORG: An Autonomous Cyber Operations Research Gym

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:52.344424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c3b7526-946c-45c2-aa8c-741ee503a7d6 · outbound

This paper cites In: TA-Explore: Teacher-Assisted Exploration for Facilitating Fast Reinforcement Learning.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations In: TA-Explore: Teacher-Assisted Exploration for Facilitating Fast Reinforcement Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:52.425782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f05a1ef-c11a-4b93-9cc9-a4ff0a16c240 · outbound

This paper cites Generalized Kullback-Leibler Divergence Loss.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations Generalized Kullback-Leibler Divergence Loss

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-08-03T01:43:37.632047Z

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 95fdd10b-e299-4581-8240-2f9c58ed1c8a · outbound

This paper cites In: Chen, Y., Lin, C.W., Chen, B., Zhu, Q.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations In: Chen, Y., Lin, C.W., Chen, B., Zhu, Q

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:52.555719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2514541c-393e-4bab-8746-2a7a73aa606f · outbound

This paper cites IJRDO -JOURNAL OF MATHEMATICS9, 1–5 (Sep 2023).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations IJRDO -JOURNAL OF MATHEMATICS9, 1–5 (Sep 2023)

Reference 7

Resolution: verified exact; doi, observed 2026-08-03T01:43:37.517742Z

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 808cc04f-9a36-4965-a46f-ca87d27ba5cb · outbound

This paper cites On Autonomous Agents in a Cyber Defence Environment.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations On Autonomous Agents in a Cyber Defence Environment

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:52.768075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 078a61a9-411e-4760-8c2a-28f300f3568a · outbound

This paper cites In: 2024 Inter- national Conference on Military Communication and Information Systems (ICM- CIS).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations In: 2024 Inter- national Conference on Military Communication and Information Systems (ICM- CIS)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:52.965086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b0a9e01-7ffc-4f4e-950c-db8a9c5e8d0b · outbound

This paper cites IEEE Computer Society (Sep 2024), https://ieeexplore-ieee- org.journal.rmc.ca/document/10645591.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations IEEE Computer Society (Sep 2024), https://ieeexplore-ieee- org.journal.rmc.ca/document/10645591

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:53.191993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2643bf3e-8666-4e7f-8a5c-43a63cb4a853 · outbound

This paper cites IEEE Ac- cess12, 120292–120305 (2024).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations IEEE Ac- cess12, 120292–120305 (2024)

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:53.308937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22293177-b667-4c70-8249-c45074af2d3d · outbound

This paper cites In: 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations In: 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:53.466971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c6e0014-b882-4034-9065-e6d34a80fed2 · outbound

This paper cites Deep Reinforcement Learning for Autonomous Cyber Defence: A Survey.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations Deep Reinforcement Learning for Autonomous Cyber Defence: A Survey

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:53.626474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 557633b9-fa7c-46bc-9d3e-59d175991dec · outbound

This paper cites IEEE Robotics and Automation Letters3(4), 4423–4430 (Oct 2018).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations IEEE Robotics and Automation Letters3(4), 4423–4430 (Oct 2018)

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:53.792216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eda13aea-b8e2-486e-bcfb-09b39ee17db2 · outbound

This paper cites https://doi.org/10.1007/s00521- 025-11162-0, https://doi.org/10.1007/s00521-025-11162-0.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations https://doi.org/10.1007/s00521- 025-11162-0, https://doi.org/10.1007/s00521-025-11162-0

Reference 15

Resolution: malformed identifier; no resolver link, observed 2026-08-03T01:39:53.885137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88cf79e1-96dc-4784-b82c-0d2b0bc969df · outbound

This paper cites In: 2025 IEEE International Conference on Fuzzy Systems (FUZZ).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations In: 2025 IEEE International Conference on Fuzzy Systems (FUZZ)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:53.996854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9715169d-f8fc-48c6-b72b-c9857e31696a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations Proximal Policy Optimization Algorithms

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:54.150659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf817027-79ec-4b81-9d74-503f92839049 · outbound

This paper cites In: 2025 IEEE Inter- national Conference on Consumer Electronics (ICCE).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations In: 2025 IEEE Inter- national Conference on Consumer Electronics (ICCE)

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:54.313818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35b43d0b-90e3-4c82-871c-9c5ccbdb7eb2 · outbound

This paper cites MIT Press, Cambridge, MA, 2nd edn.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations MIT Press, Cambridge, MA, 2nd edn

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:54.475417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4233e1c-ce95-46cf-abaa-738006603b03 · outbound

This paper cites https://github.com/Poly-AIvsAI/LLMDistillationACO (2026).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations https://github.com/Poly-AIvsAI/LLMDistillationACO (2026)

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:54.601928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1100c980-ab73-4123-bb8f-2c29f23efa7f · outbound

This paper cites In: 2025 IEEE Annual Congress on Artificial Intelligence of Things (AIoT).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations In: 2025 IEEE Annual Congress on Artificial Intelligence of Things (AIoT)

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:54.759914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3248d513-38bc-475c-ba3d-7808c20817d5 · outbound

This paper cites https://doi.org/10.48550/arXiv.2508.19278, http://arxiv.org/abs/2508.19278, arXiv:2508.19278 [cs].

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations https://doi.org/10.48550/arXiv.2508.19278, http://arxiv.org/abs/2508.19278, arXiv:2508.19278 [cs]

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-08-03T01:43:37.433367Z

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 fe97287d-64ef-479e-93f4-32ad7225ab17 · outbound

This paper cites https://doi.org/10.48550/arXiv.2509.05311, http://arxiv.org/abs/2509.05311, arXiv:2509.05311 [cs].

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations https://doi.org/10.48550/arXiv.2509.05311, http://arxiv.org/abs/2509.05311, arXiv:2509.05311 [cs]

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:54.962963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 974b8e6a-1c61-499e-ac0d-189344799cf8 · outbound

This paper cites an unresolved cited work.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:55.068987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43897768-aaad-4570-a530-9eff66f5fc70 · outbound

This paper cites IEEE Robotics and Automation Letters 10(1), 612–619 (Jan 2025).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations IEEE Robotics and Automation Letters 10(1), 612–619 (Jan 2025)

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:55.230972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d9ebcc0-c1a1-4648-8814-703f3ac9fb0e · outbound

This paper cites Algorithms17(2), 60 (Feb 2024).

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations Algorithms17(2), 60 (Feb 2024)

Reference 26

Resolution: verified exact; doi, observed 2026-08-03T01:43:37.304940Z

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 aa1939bf-9ee1-4968-9d9c-87fc36336457 · outbound

This paper cites Learning Cyber Defence Tactics from Scratch with Multi-Agent Reinforcement Learning.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations Learning Cyber Defence Tactics from Scratch with Multi-Agent Reinforcement Learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T01:39:55.512107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a5870e4-e45e-4624-8798-a91332bb8fa4 · outbound

This paper cites https://doi.org/10.48550/arXiv.2505.20335, http://arxiv.org/abs/2505.20335, arXiv:2505.20335 [cs] version: 4 20 K.

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations https://doi.org/10.48550/arXiv.2505.20335, http://arxiv.org/abs/2505.20335, arXiv:2505.20335 [cs] version: 4 20 K

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-08-03T01:43:37.193407Z

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.

Pith citing papers

No inbound Pith citation observations are available.