Pith. sign in

Paper Citation Record · LEDGER

Improving GANs by leveraging the quantum noise from real hardware

As of 10 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 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.005020Z

Source-reported events for the cited work

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.020784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.020784Z digest=sha256:10530cd3595d38bb403e6bbb5e098449bbc4f01861a424b6a7f08eac13aa782b

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.028367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.028367Z digest=sha256:6a283dcf92c021ff481a3b784d7c976ecd6c0a99ab2f86534d3daef76b2e4911

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.036663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.036663Z digest=sha256:f147b2d1ecff64060a014872471fbe926700acf9e090a50120ca86273c5c35d4

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.040450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.040450Z digest=sha256:018820dbcd34ab4a424a9bf196ed2885823045bb7976bc970256668733dff8bc

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.046775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.050548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.050548Z digest=sha256:4dcd866ab536cd1ee012716e17ca2366132b704b7e1777547f75a8a6ecf5dcdd

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:47:36.678689Z

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.

source=pdf_text observed=2026-08-06T20:47:36.059861Z digest=sha256:f04c98d155a47958ebe90f81e9d8a68ea4c82a753779f2ace7eab4492133e308

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.067729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.067729Z digest=sha256:d25096f67cb4d9fa848959b34dec36aeb6ebd90c06be3b124fcbfb0493f50aa8

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.072201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution
malformed identifier
no resolver link, observed 2026-08-06T20:47:36.076389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution
verified exact
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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T20:47:36.085144Z digest=sha256:949b596d9d2cb4c1d449dd3bfc7a03fd20c008a06a9fec3de8e86e35119c1001

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.089423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.097818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.097818Z digest=sha256:a488a6636b1688e634e3ca3b548b8bd54b8c9682e984386bd9272f2ae8e40eaf

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.103389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.103389Z digest=sha256:53c4043e503d8506b5fbdf94267f9e9c4476e30105d24007df93a37140254374

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.107192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.107192Z digest=sha256:15f4ebb343c4547567f902efd0e08ed51702a0135eddb5bfd1831bef99d02dc5

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.112236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:35.993424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:35.993424Z digest=sha256:20d00b3360916f97587dfff7ee96c6d6352a3df08b98b02baa03011294ca4646

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.024445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.024445Z digest=sha256:b5505f0209acdd5f04e021258a3def7f4d26fdf15452677da5fab68d531a28f7

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.008523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.008523Z digest=sha256:ba8cd70bd945e63bfce9eb9cabf9e22e7ecbcd0271659fc83656d57aa9fc926d

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.015936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.015936Z digest=sha256:e40f110aeaaaf949e109ee05bc7df7e3c86a07726e300efe4e8d735f1b5cfeb6

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

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

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.

source=pdf_text observed=2026-08-06T20:47:35.997191Z digest=sha256:1245b3a665741fab76a9ab320197cbc9b7047fdeac91ff0ae223d37ed708eb93

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.080170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.080170Z digest=sha256:738dedd88e81a3b79462eeb77f1a4a2524d58c74ecc06ecd61f6e93af153334f

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:36.064117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:36.064117Z digest=sha256:9f334f1b07c0d10e6c4d61cf031f9c33c9855448dd6faa5af9c488b92379faf9

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

Resolution
metadata mismatch
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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T20:47:36.012049Z digest=sha256:b3d8f0565aec9c03109e20dcd0218c7e5639a2473ac77a41a0d231b6d21ae5dd

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

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

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.

source=pdf_text observed=2026-08-05T15:33:13.114484Z digest=sha256:c2bfb9ea76286b2605d702ef2a0b27c459371be0dbc9f53f8cf01d0b7099ddef