Paper Citation Record · LEDGER

Latent Style-based Quantum GAN for high-quality Image Generation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2406.02668.

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

pith.paper-citation-record.v1
2406.02668 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:47:36.097818Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

5
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

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

Improving GANs by leveraging the quantum noise from real hardware cites this paper.

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.

Observation 5e83a6fd-2772-4b22-ba2b-12b534d1862e · inbound

Hybrid Quantum Generative Adversarial Networks To Inverse Design Metasurfaces For Incident Angle-Independent Unidirectional Transmission cites this paper.

Hybrid Quantum Generative Adversarial Networks To Inverse Design Metasurfaces For Incident Angle-Independent Unidirectional Transmission Latent Style-based Quantum GAN for high-quality Image Generation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T20:15:20.405976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02308aca-c210-4079-8aaf-28ebe63cb75b · inbound

Hybrid Quantum-Classical Inverse Design of Metasurfaces for Tailored Narrow Band Absorption cites this paper.

Hybrid Quantum-Classical Inverse Design of Metasurfaces for Tailored Narrow Band Absorption Latent Style-based Quantum GAN for high-quality Image Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T14:42:22.515572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d48eec15-b976-40c8-83a9-9b8928d25cfc · inbound

Inverse Design using Physics-Informed Quantum GANs for Tailored Absorption in Dielectric Metasurfaces cites this paper.

Inverse Design using Physics-Informed Quantum GANs for Tailored Absorption in Dielectric Metasurfaces Latent Style-based Quantum GAN for high-quality Image Generation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T14:45:37.043159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0afc2f0c-f789-4696-93c1-f2cfba3c384a · inbound

Pitfalls when tackling the exponential concentration of parameterized quantum models cites this paper.

Pitfalls when tackling the exponential concentration of parameterized quantum models Latent Style-based Quantum GAN for high-quality Image Generation

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T12:11:56.891932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86ce733d-17fa-47fa-bcf8-c2f7a0109730 · inbound

Scaling Quantum Machine Learning without Tricks: Full-Resolution and Diverse Image Generation cites this paper.

Scaling Quantum Machine Learning without Tricks: Full-Resolution and Diverse Image Generation Latent Style-based Quantum GAN for high-quality Image Generation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T20:03:57.647133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 913a4f4a-16e8-4a63-9efb-776c59e30e3d · inbound

Latent-Conditioned Parameterized Quantum Circuits as Universal Approximators for Distributions over Quantum States cites this paper.

Latent-Conditioned Parameterized Quantum Circuits as Universal Approximators for Distributions over Quantum States Latent Style-based Quantum GAN for high-quality Image Generation

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:23:24.504425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 313450c8-a3c0-46ce-8e3a-a79f9a278726 · inbound

Exponentially many initializations to avoid barren plateaus cites this paper.

Exponentially many initializations to avoid barren plateaus Latent Style-based Quantum GAN for high-quality Image Generation

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-06-27T00:00:15.260352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 50d6cffa-c3eb-427d-ae3a-260abf52129e · inbound

A Controlled Benchmark of Quantum-Latent GAN Augmentation for Brain MRI cites this paper.

A Controlled Benchmark of Quantum-Latent GAN Augmentation for Brain MRI Latent Style-based Quantum GAN for high-quality Image Generation

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:09:14.145083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.