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Paper Citation Record · LEDGER

Improving GANs by leveraging the quantum noise from real hardware

As of 17 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2507.01886.

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

pith.paper-citation-record.v1
2507.01886 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:47:36.112236Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:33:13.114484Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T15:33:13.821558Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved20
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eb6097c4-651a-4fff-aa05-4cf35bbae78e · outbound

This paper cites Generative Adversarial Networks (GANs): An Overview of Theoretical Model, Evaluation Metrics, and Recent Developments.

Improving GANs by leveraging the quantum noise from real hardware Generative Adversarial Networks (GANs): An Overview of Theoretical Model, Evaluation Metrics, and Recent Developments

Reference 5

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.005020Z digest=sha256:cde9171685fbe2bd1382aa4bd5f78f6b04a85892dea2e8720a561daaa3378a4e

Observation fd74fb05-b515-4cb9-b2c6-78d2cfbc1ee7 · outbound

This paper cites AudioGen: Textually Guided Audio Generation.

Improving GANs by leveraging the quantum noise from real hardware AudioGen: Textually Guided Audio Generation

Reference 9

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source=pdf_text observed=2026-08-06T20:47:36.020784Z digest=sha256:fb207f7c54ae92147e7beebfcb76b5c032ce8bd64b6edd52bfab16eb6e8022b9

Observation 080eedcd-92f3-4396-87eb-e2a819d30df3 · outbound

This paper cites Video to Video Generative Adversarial Network for Few-shot Learning Based on Policy Gradient.

Improving GANs by leveraging the quantum noise from real hardware Video to Video Generative Adversarial Network for Few-shot Learning Based on Policy Gradient

Reference 11

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Observation e8f15eab-235a-4363-95e2-908a7e73e12d · outbound

This paper cites Improved Training of Wasserstein GANs.

Improving GANs by leveraging the quantum noise from real hardware Improved Training of Wasserstein GANs

Reference 13

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source=pdf_text observed=2026-08-06T20:47:36.036663Z digest=sha256:ec4d85ad775dc987dd6baa2d98e373bc7f5580dd413e69f22ca1108f945f5b2f

Observation 05f3eca2-7225-4da4-af76-4120b4c61472 · outbound

This paper cites Spectral Normalization for Generative Adversarial Networks.

Improving GANs by leveraging the quantum noise from real hardware Spectral Normalization for Generative Adversarial Networks

Reference 14

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Observation 7648e9d8-8ed7-4f24-811f-97266f4ff58b · outbound

This paper cites Large Scale GAN Training for High Fidelity Natural Image Synthesis.

Improving GANs by leveraging the quantum noise from real hardware Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 15

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source=pdf_text observed=2026-08-06T20:47:36.046775Z digest=sha256:9b38e3468c882280eec07721270aed77ddcf4b650ff5e2e8a4f8032e2aa4e781

Observation eca6a50c-ae9e-4a33-8796-f136647d35e0 · outbound

This paper cites A Style-Based Generator Architecture for Generative Adversarial Networks.

Improving GANs by leveraging the quantum noise from real hardware A Style-Based Generator Architecture for Generative Adversarial Networks

Reference 16

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source=pdf_text observed=2026-08-06T20:47:36.050548Z digest=sha256:f0ce2320ce303c53088642fc27f144c0b1ec5c04c4d44cc0c3b9300e283f99a8

Observation 3376e85d-d3fa-44b6-9c54-06aaf51ae77c · outbound

This paper cites Stylegan-xl: Scaling stylegan to large di- verse datasets.

Improving GANs by leveraging the quantum noise from real hardware Stylegan-xl: Scaling stylegan to large di- verse datasets

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 2075598f-8ac4-4f58-b2b9-718cfca8ec5f · outbound

This paper cites doi: 10.1103/physrevlett.121.040502.

Improving GANs by leveraging the quantum noise from real hardware doi: 10.1103/physrevlett.121.040502

Reference 19

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Observation 85cf5728-2d7d-4720-8598-31a3d8747268 · outbound

This paper cites doi: 10.1103/physreva.98.012324.

Improving GANs by leveraging the quantum noise from real hardware doi: 10.1103/physreva.98.012324

Reference 20

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source=pdf_text observed=2026-08-06T20:47:36.072201Z digest=sha256:c296a30b215964f2a59bf572655357fab17f8bf645a008724dccfe56ccc05c00

Observation 8b19dcf9-cd23-497f-aca4-c10701cb3dfe · outbound

This paper cites an unresolved cited work.

Improving GANs by leveraging the quantum noise from real hardware Unresolved cited work

Reference 21

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source=pdf_text observed=2026-08-06T20:47:36.076389Z digest=sha256:7cbd2a93aba399cae2874eeda8aab2f37348db9b41ca025d68cb18b6c7d2c669

Observation b8bd0cf9-e96c-4c4d-a5fc-cdd0505d3fc2 · outbound

This paper cites doi: 10.1364/ opticaq.530346.

Improving GANs by leveraging the quantum noise from real hardware doi: 10.1364/ opticaq.530346

Reference 23

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doi, observed 2026-08-06T20:47:36.156917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:47:36.085144Z digest=sha256:74e40216e0ba5232760a13873adb764625cc2db6358ef28498d49cc35bb4b1e6

Observation b4db4beb-2b42-4c5f-98c8-5786c3daa689 · outbound

This paper cites Manuel S Rudolph, Sacha Lerch, Supanut Thanasilp, Oriel Kiss, Oxana Shaya, Sofia Vallecorsa, Michele Grossi, and Zoë Holmes.

Improving GANs by leveraging the quantum noise from real hardware Manuel S Rudolph, Sacha Lerch, Supanut Thanasilp, Oriel Kiss, Oxana Shaya, Sofia Vallecorsa, Michele Grossi, and Zoë Holmes

Reference 24

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source=pdf_text observed=2026-08-06T20:47:36.089423Z digest=sha256:3e54d753f222f8650cb6320ef13da4f112c857738928a274bf0774de9d996f2f

Observation 57ad8f9f-e4df-4b4b-ae33-900e4fe7a1c5 · outbound

This paper cites Latent Style-based Quantum GAN for high-quality Image Generation.

Improving GANs by leveraging the quantum noise from real hardware Latent Style-based Quantum GAN for high-quality Image Generation

Reference 26

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Observation 0a3884ab-e039-4ffd-8dcb-8765e38a0ec4 · outbound

This paper cites Variational Quantum Circuits Enhanced Generative Adversarial Network.

Improving GANs by leveraging the quantum noise from real hardware Variational Quantum Circuits Enhanced Generative Adversarial Network

Reference 27

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Observation 5fcac202-8345-48fd-9bcf-3885ef37f6b2 · outbound

This paper cites Quantum computing with Qiskit.

Improving GANs by leveraging the quantum noise from real hardware Quantum computing with Qiskit

Reference 28

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Observation de50df1b-26d7-4a54-a376-d1cc9df41a0d · outbound

This paper cites URL https:// link.aps.org/doi/10.1103/PRXQuantum.4.010327.

Improving GANs by leveraging the quantum noise from real hardware URL https:// link.aps.org/doi/10.1103/PRXQuantum.4.010327

Reference 29

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source=pdf_text observed=2026-08-06T20:47:36.112236Z digest=sha256:6f37dc860c06c5a20496ad24525e0707154cded2886e885587e2b624ef761df8

Observation c6d93b3f-ec9e-4e2a-91ca-750b4b40cce0 · outbound

This paper cites Generative Adversarial Networks.

Improving GANs by leveraging the quantum noise from real hardware Generative Adversarial Networks

Reference 2014

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Observation 93b05eb2-cdab-43bf-8f2c-7ca1f959cc3a · outbound

This paper cites Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network.

Improving GANs by leveraging the quantum noise from real hardware Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

Reference 2017

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Observation 5e6219c0-8715-46c9-9080-e437fff68ce9 · outbound

This paper cites doi: 10.1109/msp.2017.2765202.

Improving GANs by leveraging the quantum noise from real hardware doi: 10.1109/msp.2017.2765202

Reference 2018

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Observation 348f12f3-2ee2-421a-b8b8-73351e8f19e0 · outbound

This paper cites Adversarial Audio Synthesis.

Improving GANs by leveraging the quantum noise from real hardware Adversarial Audio Synthesis

Reference 2019

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Observation 12222083-7f31-4e1b-add0-606b5c14dd40 · outbound

This paper cites A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications.

Improving GANs by leveraging the quantum noise from real hardware A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

Reference 2020

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local_arxiv, observed 2026-08-06T20:47:36.648684Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 38258ad3-fcfa-4e4e-bc21-057b44d2d2a0 · outbound

This paper cites doi: 10.1103/physrevapplied.16.024051.

Improving GANs by leveraging the quantum noise from real hardware doi: 10.1103/physrevapplied.16.024051

Reference 2021

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Observation 227bc198-1a2b-4511-94e6-f7540995bec4 · outbound

This paper cites ISBN 9781450393379.

Improving GANs by leveraging the quantum noise from real hardware ISBN 9781450393379

Reference 2022

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Observation e06c4fbc-46d9-4806-97a1-35bfdb281994 · outbound

This paper cites Generative Adversarial Networks for Data Augmentation.

Improving GANs by leveraging the quantum noise from real hardware Generative Adversarial Networks for Data Augmentation

Reference 2023

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local_arxiv, observed 2026-08-06T20:47:36.545164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Pith citing papers

Observation fc176dcc-bf8c-4d3f-ae4c-2be3e5cf3f2d · inbound

Quantum latent distributions in deep generative models cites this paper.

Quantum latent distributions in deep generative models Improving GANs by leveraging the quantum noise from real hardware

Reference 23

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local_arxiv, observed 2026-08-05T15:33:13.836128Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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