Paper Citation Record · LEDGER

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing

As of 22 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2502.03086.

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

pith.paper-citation-record.v1
2502.03086 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T06:02:55.329241Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

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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

22 of 22 outbound references displayed

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verified fuzzy18
unresolved3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3c97c600-c9b4-4997-9efb-41e627b7d728 · outbound

This paper cites To- ward constructing a balanced intrusion detection dataset based on cicids2017.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing To- ward constructing a balanced intrusion detection dataset based on cicids2017

Reference 1

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Source-reported events for the cited work

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Observation ca1b0a93-f4bd-4a6a-8802-c0a747a5ab7a · outbound

This paper cites Application of Quantum Annealing to Training of Deep Neural Networks.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Application of Quantum Annealing to Training of Deep Neural Networks

Reference 2

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Source-reported events for the cited work

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Observation 11014b3c-2f25-44e5-a805-b7a0d8b5dbd1 · outbound

This paper cites Quantum boltzmann machine.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Quantum boltzmann machine

Reference 3

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Source-reported events for the cited work

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Observation da02b9eb-c544-4a58-8737-17477f389150 · outbound

This paper cites Estimation of effective temperatures in quantum anneal- ers for sampling applications: A case study with restricted boltzmann machines.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Estimation of effective temperatures in quantum anneal- ers for sampling applications: A case study with restricted boltzmann machines

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.793149Z

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Observation 79c81f0c-5d56-448b-9d2a-c81192c77794 · outbound

This paper cites The ising model: teaching an old problem new tricks.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing The ising model: teaching an old problem new tricks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.777904Z

Source-reported events for the cited work

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Observation 67f93a0b-e779-460f-9ee4-30909b1ae8aa · outbound

This paper cites Explaining the gibbs sampler.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Explaining the gibbs sampler

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.760910Z

Source-reported events for the cited work

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Observation c3d86e7b-528c-483b-8f29-ae822a84b65b · outbound

This paper cites Smote: synthetic minority over-sampling technique.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Smote: synthetic minority over-sampling technique

Reference 7

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Source-reported events for the cited work

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Observation ab68ed46-f371-4aa4-9051-2078465735f6 · outbound

This paper cites Pegasus: The second connectivity graph for large-scale quantum annealing hardware.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Pegasus: The second connectivity graph for large-scale quantum annealing hardware

Reference 8

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Observation 1137c3e7-9761-49d7-80e6-2cfc490e2b53 · outbound

This paper cites Quantum-assisted training of restricted boltzmann machines.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Quantum-assisted training of restricted boltzmann machines

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.719101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c7bdf57a-375d-48fb-9aa7-605285a14f12 · outbound

This paper cites On the effectiveness of preprocessing methods when dealing with different levels of class imbalance.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing On the effectiveness of preprocessing methods when dealing with different levels of class imbalance

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.676257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f27896d0-c9a0-45e5-8b4e-e1ed22f2ab2e · outbound

This paper cites Balancing approaches towards ml for ids: a survey for the cse-cic ids dataset.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Balancing approaches towards ml for ids: a survey for the cse-cic ids dataset

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.660696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ce6ad6a8-bf35-4393-a07c-712a051130ed · outbound

This paper cites Learning from imbalanced data.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Learning from imbalanced data

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.609907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8f826251-5b14-44aa-b6f1-05f2a76e2cfd · outbound

This paper cites Training products of experts by minimizing contrastive divergence.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Training products of experts by minimizing contrastive divergence

Reference 13

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Source-reported events for the cited work

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Observation 93e446c2-cb37-43c6-b704-8ac7b2b93c48 · outbound

This paper cites A practical guide to training restricted boltzmann machines.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing A practical guide to training restricted boltzmann machines

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.580249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fd326ed4-524f-48fa-bb10-eb92f49eba5a · outbound

This paper cites Reducing the dimen- sionality of data with neural networks.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Reducing the dimen- sionality of data with neural networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.566224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 25d221d6-6adc-4979-8e0f-b27d022993cf · outbound

This paper cites Pegasus topology, 2020.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Pegasus topology, 2020

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.548516Z

Source-reported events for the cited work

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Observation 71403a81-89a8-49ac-b2f9-68dfea23d01e · outbound

This paper cites Characterization of tor traffic using time based features.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Characterization of tor traffic using time based features

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.529647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a98af945-1783-4b81-abd8-ab93765e7fc9 · outbound

This paper cites Data-balancing algorithm based on generative adversarial network for robust network intrusion detection.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Data-balancing algorithm based on generative adversarial network for robust network intrusion detection

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.510613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 46b4c726-f84f-4129-b219-0111c9a9ff20 · outbound

This paper cites Machine learning with oversampling and undersampling techniques: overview study and experimental results.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Machine learning with oversampling and undersampling techniques: overview study and experimental results

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.479094Z

Source-reported events for the cited work

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Observation 1a1da267-d9c4-4ff0-bbb4-70b35ae72bbf · outbound

This paper cites 4-clique Network Minor Embedding for Quantum Annealers.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing 4-clique Network Minor Embedding for Quantum Annealers

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-09T06:02:55.378979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 40a5521c-d653-479e-abd5-4156439d095f · outbound

This paper cites To- ward generating a new intrusion detection dataset and intrusion traffic characterization.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing To- ward generating a new intrusion detection dataset and intrusion traffic characterization

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.462532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2fce1407-9d1e-4edf-9f28-db2a390bc88b · outbound

This paper cites Quan- tum optimization of fully connected spin glasses.

Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing Quan- tum optimization of fully connected spin glasses

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T06:02:55.440398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.