Paper Citation Record · LEDGER

GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1810.10863.

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

pith.paper-citation-record.v1
1810.10863 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 2026-08-13T06:32:02.005865+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:51:55.001663Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T13:48:20.936271Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 318ab49d-f04c-40ab-a1ac-f527f02a1857 · inbound

A Realistic Collimated X-Ray Image Simulation Pipeline cites this paper.

A Realistic Collimated X-Ray Image Simulation Pipeline GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T19:51:55.001663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bb0c5b2-8eb8-4099-a7ea-cfea31e2584a · inbound

OccScene: Semantic Occupancy-based Cross-task Mutual Learning for 3D Scene Generation cites this paper.

OccScene: Semantic Occupancy-based Cross-task Mutual Learning for 3D Scene Generation GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T15:17:38.668391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 603b05ca-3555-4b75-bb76-6417d4e7406c · inbound

Relevance-driven Input Dropout: an Explanation-guided Regularization Technique cites this paper.

Relevance-driven Input Dropout: an Explanation-guided Regularization Technique GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T13:35:50.658733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 138d14ce-e4b6-4885-b0c6-1aa6b44d4f49 · inbound

Prompt Mechanisms in Medical Imaging: A Comprehensive Survey cites this paper.

Prompt Mechanisms in Medical Imaging: A Comprehensive Survey GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Reference 167

Resolution: unresolved; no resolver link, observed 2026-08-06T22:02:25.508467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66bca5df-34b1-4b80-9f5d-fb573325ffa7 · inbound

Reading a Ruler in the Wild cites this paper.

Reading a Ruler in the Wild GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T18:53:48.805962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e8502ce-e96f-44b9-9524-534a8a0257c8 · inbound

Bringing Balance to Hand Shape Classification: Mitigating Data Imbalance Through Generative Models cites this paper.

Bringing Balance to Hand Shape Classification: Mitigating Data Imbalance Through Generative Models GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T15:03:48.511677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2cf5bec-3330-4be4-8828-f8c052630b76 · inbound

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method cites this paper.

Scaling Up Occupancy-centric Driving Scene Generation: Dataset and Method GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T08:07:37.201301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 938a8f11-b6cc-4d76-a3d5-4585227e8376 · inbound

Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Training cites this paper.

Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Training GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:29.348864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 953d9ba1-e0bb-4382-b040-6bc71d02ea25 · inbound

To GAN or Not To GAN: Segmentation Analysis on Mars DEM cites this paper.

To GAN or Not To GAN: Segmentation Analysis on Mars DEM GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-07-03T13:48:20.937439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.