Paper Citation Record · LEDGER

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning

As of 10 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2506.04454.

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

pith.paper-citation-record.v1
2506.04454 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:46:22.462785Z

measured 34 of 34 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T18:04:09.528381Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T18:06:43.032769Z

Reference resolution

33 of 33 outbound references displayed

verified exact1
verified fuzzy21
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cdfff4b9-01f0-4ba9-97ea-6138e6087f2e · outbound

This paper cites An intelligent tree-based intrusion detection model for cyber security.Journal of Network and Systems Management, 29(2):20, 2021.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning An intelligent tree-based intrusion detection model for cyber security.Journal of Network and Systems Management, 29(2):20, 2021

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.782016Z

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.

Observation e05ac072-56bc-4b52-85f2-a141e3b8d751 · outbound

This paper cites an unresolved cited work.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:46:22.773076Z

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.

Observation d3b9615a-d1b7-40b9-9d9b-e3337497f174 · outbound

This paper cites an unresolved cited work.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:46:22.763925Z

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.

Observation 2f1db8cc-1525-4444-9572-a734c82a1819 · outbound

This paper cites Application of image processing and transfer learning for the detection of rust disease.Scientific Reports, 13(1):5133, 2023.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Application of image processing and transfer learning for the detection of rust disease.Scientific Reports, 13(1):5133, 2023

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.755000Z

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.

Observation 61d398b0-b58c-4579-8ea8-81e4b754a187 · outbound

This paper cites an unresolved cited work.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:46:22.746114Z

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.

Observation 9c2c6e6a-6503-40ec-91a9-d6581241142f · outbound

This paper cites Multimodal Transfer Deep Learning with Applications in Audio-Visual Recognition.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Multimodal Transfer Deep Learning with Applications in Audio-Visual Recognition

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T10:46:22.369091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4683aa95-7874-4495-b321-6bbfdc9e1111 · outbound

This paper cites Transfer learning for medical image classification: a literature review.BMC medical imaging, 22(1):69, 2022.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Transfer learning for medical image classification: a literature review.BMC medical imaging, 22(1):69, 2022

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.737280Z

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.

Observation b86d1ca9-37bc-4734-8180-6498a9033378 · outbound

This paper cites An intrusion-detection model.IEEE Transactions on software engineering, SE-13(2):222– 232, 1987.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning An intrusion-detection model.IEEE Transactions on software engineering, SE-13(2):222– 232, 1987

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.728414Z

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.

Observation 42f637a1-e1d8-40e3-8b8d-279db925c077 · outbound

This paper cites Generalized out-of-distribution detection: A survey.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Generalized out-of-distribution detection: A survey

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.719054Z

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.

Observation 554d5731-cfa3-4a50-bf4d-a86280d8c252 · outbound

This paper cites Pavlik, and Nathaniel D.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Pavlik, and Nathaniel D

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.710240Z

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.

Observation f6e9e4a5-c67a-45a2-b850-03fb72705bb7 · outbound

This paper cites Unsw-nb15: A comprehensive data set for network intrusion detection systems (unsw-nb15 network data set).

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Unsw-nb15: A comprehensive data set for network intrusion detection systems (unsw-nb15 network data set)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.701617Z

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.

Observation 921379c7-9d3d-4971-a34b-e3e7be744d24 · outbound

This paper cites Toward generating a new intrusion detection dataset and intrusion traffic characterization.ICISSp, 1:108–116, 2018.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Toward generating a new intrusion detection dataset and intrusion traffic characterization.ICISSp, 1:108–116, 2018

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.691257Z

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.

Observation d0126981-c52b-4610-91dc-f96610c6e970 · outbound

This paper cites Aci iot network traffic dataset 2023, Apr 2024.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Aci iot network traffic dataset 2023, Apr 2024

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.682719Z

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.

Observation a173ca98-0a5f-44a0-bc70-650b6bdd79df · outbound

This paper cites A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T10:46:22.395273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94f5a1e6-0573-4b0f-a634-62957dcbd085 · outbound

This paper cites Surgical Fine-Tuning Improves Adaptation to Distribution Shifts.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T10:46:22.398872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86ef9fd1-a7f4-4e37-861e-0537a2db17bc · outbound

This paper cites Transtailor: Pruning the pre-trained model for improved transfer learning.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Transtailor: Pruning the pre-trained model for improved transfer learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.673905Z

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.

Observation 224525f6-3e22-4e62-bf7f-cbc36f068f36 · outbound

This paper cites Spottune: Transfer learning through adaptive fine-tuning.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Spottune: Transfer learning through adaptive fine-tuning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.664825Z

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.

Observation a17d3b1e-1bf8-4f53-9cd3-daf12c01a8ac · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T10:46:22.416174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aba589ea-ed53-48d0-bde2-49364ab6395e · outbound

This paper cites Wong, Alexander M.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Wong, Alexander M

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.655822Z

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.

Observation d753d957-7a75-4c14-95e7-61ca6b59f4d0 · outbound

This paper cites Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T10:46:22.501289Z

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.

Observation a1023e6d-72bd-4882-bff2-1934261b7696 · outbound

This paper cites Confidence scoring using whitebox meta-models with linear classifier probes.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Confidence scoring using whitebox meta-models with linear classifier probes

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.646159Z

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.

Observation 51f2d344-2487-4279-b095-32549bbfef6d · outbound

This paper cites Lundberg and Su-In Lee.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Lundberg and Su-In Lee

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.636784Z

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.

Observation 1eea3d16-f570-4cb8-8377-eab915e325cc · outbound

This paper cites Ross Quinlan.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Ross Quinlan

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.626029Z

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.

Observation dd2cdf5f-6159-4946-93e2-41e7d955fe95 · outbound

This paper cites Unsupervised deep embedding for clustering analysis.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Unsupervised deep embedding for clustering analysis

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.617046Z

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.

Observation 9a84b8ad-feae-49be-9bf3-661217eb91c1 · outbound

This paper cites Xgboost: A scalable tree boosting system.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Xgboost: A scalable tree boosting system

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.607406Z

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.

Observation e96355de-0da0-4f12-9d85-72bc2a77e2e7 · outbound

This paper cites Quantifying information flow using min-entropy.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Quantifying information flow using min-entropy

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.598208Z

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.

Observation 290a6fc2-7743-470d-88bf-2371d0dd4740 · outbound

This paper cites Single-model uncertainties for deep learning.Advances in Neural Information Processing Systems, 32:6415–6425, 2019.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Single-model uncertainties for deep learning.Advances in Neural Information Processing Systems, 32:6415–6425, 2019

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.588761Z

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.

Observation 61c19d39-b207-4f29-a844-2f9e2f03b04d · outbound

This paper cites Lundberg, Gabriel G.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Lundberg, Gabriel G

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T10:46:22.449901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 067caca2-7d9d-4f7b-9238-1e423b6ddccd · outbound

This paper cites From local explanations to global understanding with explainable ai for trees.Nature machine intelligence, 2(1):56–67, 2020.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning From local explanations to global understanding with explainable ai for trees.Nature machine intelligence, 2(1):56–67, 2020

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T10:46:22.453573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c48bc1b-3a91-46a4-a1dd-e21443b411dc · outbound

This paper cites The use of the area under the roc curve in the evaluation of machine learning algorithms.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning The use of the area under the roc curve in the evaluation of machine learning algorithms

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.568286Z

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.

Observation 71e71c9f-1061-46e8-be71-2a6a8f0adcd3 · outbound

This paper cites Bastian, Daniel Clouse, Bradford Kline, and Susmit Jha.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning Bastian, Daniel Clouse, Bradford Kline, and Susmit Jha

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:46:22.558502Z

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.

Observation 101ba47d-311f-45e9-bd23-63be135c6cbf · outbound

This paper cites ACI IoT Network Traffic Dataset 2023.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning ACI IoT Network Traffic Dataset 2023

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T10:46:22.462785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f1c03c4-de75-49e5-afbd-c6233a8a0f7b · outbound

This paper cites URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks.

Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks

Reference 2020

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:46:22.522770Z

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.

Pith citing papers

Observation dfd2f5d3-cc20-469b-8652-1596ff94b221 · inbound

Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities cites this paper.

Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:06:43.035734Z

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.