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Paper Citation Record · LEDGER

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations

As of 15 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2607.26201.

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

pith.paper-citation-record.v1
2607.26201 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T00:34:16.882059Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

35 of 35 outbound references displayed

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External citation measurements

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Outbound references

Observation 36076810-204d-411a-b297-3a19ea9e2295 · outbound

This paper cites Scientific Reports15(1), 1726 (2025).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Scientific Reports15(1), 1726 (2025)

Reference 1

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Observation 70114883-cfd8-4228-9a17-6139c0b94cb6 · outbound

This paper cites frontiers in computer science, 6 (2024).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations frontiers in computer science, 6 (2024)

Reference 2

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source=pdf_text observed=2026-08-01T00:34:16.310684Z digest=sha256:34a0c46748f9e5cb73e954331f5df11c91aaf9d721792d51cea1872517c7b67e

Observation bdd57197-11b0-4211-9200-eca1a59b46c4 · outbound

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

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs)

Reference 3

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Observation 41b0b726-31bc-4ed4-b46d-657d16900a39 · outbound

This paper cites Information fusion58, 82–115 (2020).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Information fusion58, 82–115 (2020)

Reference 4

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source=pdf_text observed=2026-08-01T00:34:16.521211Z digest=sha256:b07929044563ca81f5f141b4895315c4d69a64a6fc05761deef36e61b3df9bb0

Observation 3c4730da-1b34-4f90-bee9-b750bb43d336 · outbound

This paper cites AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum

Reference 5

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source=pdf_text observed=2026-08-01T00:34:16.651254Z digest=sha256:59153babc70357412d88fa22f2fd64cea195dbd1fb286f64b0799b312a916f34

Observation 432be145-f11d-478c-8374-f3a5cb81cbb3 · outbound

This paper cites Thinking Machines: A Survey of LLM based Reasoning Strategies.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Thinking Machines: A Survey of LLM based Reasoning Strategies

Reference 6

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source=pdf_text observed=2026-08-01T00:34:16.749687Z digest=sha256:d1506a3257d4ab1071091ee284d101864d4fbc4747e135795f5ac3b224ea4e18

Observation c65506d2-325d-40fd-9cff-48d4a61d83f7 · outbound

This paper cites In: 2024 IEEE 10th World Forum on Internet of Things (WF-IoT).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations In: 2024 IEEE 10th World Forum on Internet of Things (WF-IoT)

Reference 7

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source=pdf_text observed=2026-08-01T00:34:16.755193Z digest=sha256:a8d1ea5616ac3c628ea8292c2f79ec673ad609bf3fe70601796f7d529f7622b8

Observation c1e2dcad-5f28-49e5-bc35-aff205eabdb9 · outbound

This paper cites Journal of Cybersecurity and Privacy4(4), 777– 793 (2024).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Journal of Cybersecurity and Privacy4(4), 777– 793 (2024)

Reference 8

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source=pdf_text observed=2026-08-01T00:34:16.759523Z digest=sha256:d44664ebd33c30130aa831c11939c1b000a906d86b40592669fa2808f83080d9

Observation 8c66491f-1d4a-49b4-8fd2-c5e09696c347 · outbound

This paper cites Interpretable Anomaly-Based DDoS Detection in AI-RAN with XAI and LLMs.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Interpretable Anomaly-Based DDoS Detection in AI-RAN with XAI and LLMs

Reference 9

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source=pdf_text observed=2026-08-01T00:34:16.763747Z digest=sha256:b0d9ea0dbfc6ab741980dbc17192ffb0785a4bc49338b6d180cee9ee9d9d3dc5

Observation 57cdcdd2-95b5-47de-aa1a-816b2859b8cc · outbound

This paper cites NIST Special Publication800(61), 1–147 (2012).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations NIST Special Publication800(61), 1–147 (2012)

Reference 10

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Observation 73c833e5-8f27-4535-a4ad-a93089a40c0e · outbound

This paper cites Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey

Reference 11

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source=pdf_text observed=2026-08-01T00:34:16.772694Z digest=sha256:674dd22db72fe3967cdaea569cf970a3fff4c9c73b6659cf6e75f6d4eac3cf16

Observation b02a031f-8530-4294-886e-2dcbb7c5f6c0 · outbound

This paper cites Computers and Electrical Engineering129, 110826 (2026).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Computers and Electrical Engineering129, 110826 (2026)

Reference 12

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Observation 47d0e22f-37f3-44be-b122-e780c0638e76 · outbound

This paper cites Towards Explainable Network Intrusion Detection using Large Language Models.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Towards Explainable Network Intrusion Detection using Large Language Models

Reference 13

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Observation ca1e6318-4e29-4c40-9257-c84e2783a3ad · outbound

This paper cites an unresolved cited work.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Unresolved cited work

Reference 14

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Observation 7ea067b1-c198-412a-a77d-ef38e60b9ca3 · outbound

This paper cites an unresolved cited work.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Unresolved cited work

Reference 15

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source=pdf_text observed=2026-08-01T00:34:16.790318Z digest=sha256:9e945498230cbaa18680834db2ada0790aee20d14f5827849d910fcde3f080b5

Observation c4984bb6-36df-4503-8ef3-34e1f2deb448 · outbound

This paper cites Computers & Security95, 101851 (2020).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Computers & Security95, 101851 (2020)

Reference 16

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Observation 5f6df651-9dc5-4998-b1e9-4f5cb2166c14 · outbound

This paper cites EXPLICATE: Enhancing Phishing Detection through Explainable AI and LLM-Powered Interpretability.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations EXPLICATE: Enhancing Phishing Detection through Explainable AI and LLM-Powered Interpretability

Reference 17

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Observation 19b109a3-1516-4ec5-8ab7-b38c731ab29a · outbound

This paper cites Advances in neural information processing systems30(2017).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Advances in neural information processing systems30(2017)

Reference 18

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Observation f7c81fd1-865f-4f04-8a07-ca4507920a48 · outbound

This paper cites arXiv preprint arXiv:2508.21323 (2025).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations arXiv preprint arXiv:2508.21323 (2025)

Reference 19

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Observation 0af3e86d-f969-450a-9ed7-15ed257afdb4 · outbound

This paper cites In: 2024 5th International Conference in Electronic Engineering, Information Technology & Education (EEITE).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations In: 2024 5th International Conference in Electronic Engineering, Information Technology & Education (EEITE)

Reference 20

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Observation e3c31517-1c46-48ac-8d39-4e8ef141f721 · outbound

This paper cites Journal of Cybersecurity and Privacy5(3), 55 (2025).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Journal of Cybersecurity and Privacy5(3), 55 (2025)

Reference 21

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Observation 35d2ea85-babf-4954-8c52-4e1cac8a4eb9 · outbound

This paper cites an unresolved cited work.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Unresolved cited work

Reference 22

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source=pdf_text observed=2026-08-01T00:34:16.820927Z digest=sha256:2b7575f579022531773c5475a5b2be7c8c2d9ec7ef81fdcd94f33ea460edfb81

Observation e0df9f39-98fe-46fd-8aeb-701ff9517751 · outbound

This paper cites an unresolved cited work.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Unresolved cited work

Reference 23

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Observation ef644fc4-0caa-436d-bf0a-5ed57b3d65ae · outbound

This paper cites Cognitive Systems Research86, 101243 (2024).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Cognitive Systems Research86, 101243 (2024)

Reference 24

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Observation e62fab2a-0dec-4ad6-b759-6f584a4580e2 · outbound

This paper cites why should i trust you?.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations why should i trust you?

Reference 25

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Observation b17b3704-1b43-4759-9604-f80c18c9d099 · outbound

This paper cites ICT express10(4), 935–958 (2024).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations ICT express10(4), 935–958 (2024)

Reference 26

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Observation ac5e943a-8d01-465a-a615-d8c0b64b24cd · outbound

This paper cites ICISSp1(2018), 108–116 (2018).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations ICISSp1(2018), 108–116 (2018)

Reference 27

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Observation db6333e2-cadf-44c1-aa2e-616cd1af0d2c · outbound

This paper cites Journal of Cybersecurity and Privacy5(4), 95 (2025).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Journal of Cybersecurity and Privacy5(4), 95 (2025)

Reference 28

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Observation 6e4d9b70-66df-4b1b-829f-72c2ff77d2d8 · outbound

This paper cites ACM Computing Surveys 57(9), 1–38 (2025).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations ACM Computing Surveys 57(9), 1–38 (2025)

Reference 29

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source=pdf_text observed=2026-08-01T00:34:16.852350Z digest=sha256:26634f4434b5c4ce395f32cc02793b59daea643649975cc7dec2b3fbd89c5e0e

Observation 43d544cc-b658-4903-84ee-08a7355cf652 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Gemini: A Family of Highly Capable Multimodal Models

Reference 30

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Observation b5d5548f-d2ff-4a2a-9a06-8011943e9e7e · outbound

This paper cites Ieee Access8, 227756–227779 (2020).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Ieee Access8, 227756–227779 (2020)

Reference 31

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Observation 131d4296-ba76-4c0a-a6d5-7a0c697e5d25 · outbound

This paper cites In: 2019 IEEE International Conference on Electro Informa- tion Technology (EIT).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations In: 2019 IEEE International Conference on Electro Informa- tion Technology (EIT)

Reference 32

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Observation ad6d91a4-4de0-42a8-b08d-3e69abec742d · outbound

This paper cites In: 2024 12th International Symposium on Digital Forensics and Security (ISDFS).

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations In: 2024 12th International Symposium on Digital Forensics and Security (ISDFS)

Reference 33

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Observation 81b3795a-4633-468c-abf4-5afb831d0834 · outbound

This paper cites an unresolved cited work.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations Unresolved cited work

Reference 34

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Observation fee6fc73-1bab-4191-ba13-ab7435ecb35f · outbound

This paper cites 4 DLdeep learning.

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations 4 DLdeep learning

Reference 35

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Pith citing papers

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