Paper Citation Record · LEDGER

Training Generative Adversarial Networks with Limited Data

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2006.06676.

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

pith.paper-citation-record.v1
2006.06676 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T23:05:15.623022Z

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

937
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 0dfba287-75ba-4305-81f5-100361691db7 · inbound

Denoising Diffusion Probabilistic Models cites this paper.

Denoising Diffusion Probabilistic Models Training Generative Adversarial Networks with Limited Data

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T03:24:24.842262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0e1f231e-fb18-402e-9ca9-89327ea907fb · inbound

Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed cites this paper.

Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed Training Generative Adversarial Networks with Limited Data

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-17T03:56:19.939966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9958c1e6-1ec2-4584-b27f-4abd8ea52529 · inbound

SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations cites this paper.

SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations Training Generative Adversarial Networks with Limited Data

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T22:30:44.815418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1bd186f3-2c3f-4dd6-818e-84e53dea81ba · inbound

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network cites this paper.

Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network Training Generative Adversarial Networks with Limited Data

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T23:05:15.623022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d3febca-dd67-4ff5-9ea7-10e233f8b567 · inbound

Beyond and Free from Diffusion: Invertible Guided Consistency Training cites this paper.

Beyond and Free from Diffusion: Invertible Guided Consistency Training Training Generative Adversarial Networks with Limited Data

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T19:41:03.323833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eaef7edc-3f41-4ab3-9b2f-bcc0cfbc52fc · inbound

Discrete Markov Bridge cites this paper.

Discrete Markov Bridge Training Generative Adversarial Networks with Limited Data

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T14:17:13.923032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f2e4b3b-04e5-4a25-a22b-cda0d1038d73 · inbound

Learning from Limited and Imperfect Data cites this paper.

Learning from Limited and Imperfect Data Training Generative Adversarial Networks with Limited Data

Reference 143

Resolution: unresolved; no resolver link, observed 2026-08-06T13:10:01.279856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34f99ce0-bc2e-484d-8ebc-1312c31e4719 · inbound

Case Studies of Generative Machine Learning Models for Dynamical Systems cites this paper.

Case Studies of Generative Machine Learning Models for Dynamical Systems Training Generative Adversarial Networks with Limited Data

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T00:01:46.953088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aff06c15-b8e5-4a50-b24b-e677b22a604d · inbound

SPRINT: Robust Model Attribution of Generated Images via Secret Pixel Reconstruction cites this paper.

SPRINT: Robust Model Attribution of Generated Images via Secret Pixel Reconstruction Training Generative Adversarial Networks with Limited Data

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-19T00:42:54.517191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d481f497-022d-49b8-a5d2-ebe09e44e08c · inbound

Mitigating Data Scarcity in Spaceflight Applications for Offline Reinforcement Learning Using Physics-Informed Deep Generative Models cites this paper.

Mitigating Data Scarcity in Spaceflight Applications for Offline Reinforcement Learning Using Physics-Informed Deep Generative Models Training Generative Adversarial Networks with Limited Data

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T21:38:18.434636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5614161c-646d-49d6-b99b-02a1fbb346de · inbound

A Wasserstein GAN-based climate scenario generator for risk management and insurance: the case of soil subsidence cites this paper.

A Wasserstein GAN-based climate scenario generator for risk management and insurance: the case of soil subsidence Training Generative Adversarial Networks with Limited Data

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T01:45:51.891395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4600c926-9220-4bb7-b987-673f735746d8 · inbound

Generating Financial Time Series by Matching Random Convolutional Features cites this paper.

Generating Financial Time Series by Matching Random Convolutional Features Training Generative Adversarial Networks with Limited Data

Reference 119

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T07:26:45.992436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.