Paper Citation Record · LEDGER

Large Scale GAN Training for High Fidelity Natural Image Synthesis

As of 12 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 100 inbound Pith citation observations for arXiv:1809.11096.

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

pith.paper-citation-record.v1
1809.11096 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-13T12:11:19.361655Z

measured 134 of 134 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 100 of 141 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:59:25.109699Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

34 of 34 outbound references displayed

verified exact10
verified fuzzy18
unresolved5
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External citation measurements

2430
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 52c73695-243c-4c45-b6bf-d31450fb9a28 · outbound

This paper cites A Note on the Inception Score.

Large Scale GAN Training for High Fidelity Natural Image Synthesis A Note on the Inception Score

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.423171Z

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Observation f4056657-2a25-4ee0-9cd6-c7ed33159d81 · outbound

This paper cites The Cramer Distance as a Solution to Biased Wasserstein Gradients.

Large Scale GAN Training for High Fidelity Natural Image Synthesis The Cramer Distance as a Solution to Biased Wasserstein Gradients

Reference 2

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Observation 697ff4ea-cdf6-4dea-8d98-0b247184d57a · outbound

This paper cites Dai, Shakir Mohamed, and Ian Goodfellow.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Dai, Shakir Mohamed, and Ian Goodfellow

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.459601Z

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Observation f3d9d5a3-4bd7-4855-8007-9e455b20c51d · outbound

This paper cites On Convergence and Stability of GANs.

Large Scale GAN Training for High Fidelity Natural Image Synthesis On Convergence and Stability of GANs

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.412685Z

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Observation a0b9c04d-596d-4911-9cca-ef99b00da413 · outbound

This paper cites Geometric GAN.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Geometric GAN

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.389309Z

Source-reported events for the cited work

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Observation dce8cca5-6c80-4c59-9dc8-63d32063c683 · outbound

This paper cites Least Squares Generative Adversarial Networks.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Least Squares Generative Adversarial Networks

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.393389Z

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Observation 3d31801b-1141-43df-8c02-7eace4a22ab3 · outbound

This paper cites Megapixel Size Image Creation using Generative Adversarial Networks.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Megapixel Size Image Creation using Generative Adversarial Networks

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-04T21:59:00.312797Z

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Observation 6ae4f6b9-5bc0-4033-9559-6117a0044261 · outbound

This paper cites Conditional Generative Adversarial Nets.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Conditional Generative Adversarial Nets

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-13T12:11:19.400347Z

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Observation f139f09d-17bc-401e-9206-07bda99718d9 · outbound

This paper cites Brown, Christopher Olah, Colin Raf- fel, and Ian Goodfellow.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Brown, Christopher Olah, Colin Raf- fel, and Ian Goodfellow

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.462167Z

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Observation ba515b2e-fc93-42e2-9a10-45847c1db1de · outbound

This paper cites Comparing Generative Adversarial Network Techniques for Image Creation and Modification.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Comparing Generative Adversarial Network Techniques for Image Creation and Modification

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-04T22:38:51.828537Z

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Observation 6d68df56-f54a-439c-b3bd-1c230c44a513 · outbound

This paper cites Dropout: A simple way to prevent neural networks from overﬁtting.JMLR, 15:1929–1958.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Dropout: A simple way to prevent neural networks from overﬁtting.JMLR, 15:1929–1958

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.465344Z

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Observation c83aa40d-52f0-4768-be45-bac3cf63fcd7 · outbound

This paper cites A note on the evaluation of generative models.

Large Scale GAN Training for High Fidelity Natural Image Synthesis A note on the evaluation of generative models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.416250Z

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Observation 2acf0412-f618-40cf-ae27-17209a30db69 · outbound

This paper cites The Unusual Effectiveness of Averaging in GAN Training.

Large Scale GAN Training for High Fidelity Natural Image Synthesis The Unusual Effectiveness of Averaging in GAN Training

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-04T23:25:17.078416Z

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Observation 25103832-cfa0-4a0e-bbe7-af5e91fbce1d · outbound

This paper cites Self-Attention Generative Adversarial Networks.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Self-Attention Generative Adversarial Networks

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.384919Z

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Observation 75ba8fbd-bb86-4da7-8376-3318670540bf · outbound

This paper cites Figure 6: Samples generated by our BigGAN model at 512×512 resolution.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Figure 6: Samples generated by our BigGAN model at 512×512 resolution

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.468218Z

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Observation f64a335b-dcf1-4b14-b7b7-fe33a7d7ae94 · outbound

This paper cites The generated image is in the top left.

Large Scale GAN Training for High Fidelity Natural Image Synthesis The generated image is in the top left

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.470540Z

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Observation 3f894a67-0e9c-4a0b-8b6f-95c43cfc32cc · outbound

This paper cites The generated image is in the top left.

Large Scale GAN Training for High Fidelity Natural Image Synthesis The generated image is in the top left

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.473294Z

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Observation f3bf31ff-9c23-4128-807b-b89cad5512a0 · outbound

This paper cites The generated image is in the top left.

Large Scale GAN Training for High Fidelity Natural Image Synthesis The generated image is in the top left

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.475876Z

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Observation 46645ad2-8124-445e-bd46-2f85def16d47 · outbound

This paper cites (2018); Gulrajani et al.

Large Scale GAN Training for High Fidelity Natural Image Synthesis (2018); Gulrajani et al

Reference 19

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Observation 79fc82ae-a23f-41a2-9bf7-776b2c44031b · outbound

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Large Scale GAN Training for High Fidelity Natural Image Synthesis Unresolved cited work

Reference 20

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Observation a5551de8-2b5e-4dba-893b-9347aba6dbb1 · outbound

This paper cites Relative to the 256× 256 architecture, we add an additional ResBlock at the 512× 512 resolution.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Relative to the 256× 256 architecture, we add an additional ResBlock at the 512× 512 resolution

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.483035Z

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Observation 3a58dc41-0d63-4a7b-b39b-b46c00628e88 · outbound

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Large Scale GAN Training for High Fidelity Natural Image Synthesis Unresolved cited work

Reference 22

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Large Scale GAN Training for High Fidelity Natural Image Synthesis Unresolved cited work

Reference 23

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Observation 7df0842e-b1f5-4225-ac54-e9048589c56a · outbound

This paper cites We employ the architectures detailed in Appendix B, with non-local blocks inserted at a single stage in each network.

Large Scale GAN Training for High Fidelity Natural Image Synthesis We employ the architectures detailed in Appendix B, with non-local blocks inserted at a single stage in each network

Reference 24

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Observation 2c987d58-783a-4822-8852-cdffe5d2b559 · outbound

This paper cites We train on a Google TPU v3 Pod, with the number of cores proportional to the resolution: 128 for 128×128, 256 for 256×256, and 512 for 512×512.

Large Scale GAN Training for High Fidelity Natural Image Synthesis We train on a Google TPU v3 Pod, with the number of cores proportional to the resolution: 128 for 128×128, 256 for 256×256, and 512 for 512×512

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.434772Z

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Observation cd2ef668-af22-4bcd-914a-6ca6e900011b · outbound

This paper cites 23 Published as a conference paper at ICLR 2019 APPENDIX D A DDITIONAL PLOTS Figure 17: IS vs.

Large Scale GAN Training for High Fidelity Natural Image Synthesis 23 Published as a conference paper at ICLR 2019 APPENDIX D A DDITIONAL PLOTS Figure 17: IS vs

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.437440Z

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Observation d611f88f-3f4f-40f4-ac5e-a33209ad99b9 · outbound

This paper cites FID at 256 ×256.

Large Scale GAN Training for High Fidelity Natural Image Synthesis FID at 256 ×256

Reference 27

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Observation 64616707-755e-4e58-8844-c0a98088cde5 · outbound

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Large Scale GAN Training for High Fidelity Natural Image Synthesis Unresolved cited work

Reference 28

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Observation ee1dc0b0-1be3-4c7b-9f2f-76b37bf0e5cc · outbound

This paper cites 28 Published as a conference paper at ICLR 2019 (a)σ0 (b) σ0 σ1 (c)σ1 (d)σ2 Figure 23: G training statistics with an R1 Gradient Penalty of strength 10 on D.

Large Scale GAN Training for High Fidelity Natural Image Synthesis 28 Published as a conference paper at ICLR 2019 (a)σ0 (b) σ0 σ1 (c)σ1 (d)σ2 Figure 23: G training statistics with an R1 Gradient Penalty of strength 10 on D

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.445106Z

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Observation fb5a94ac-64f1-44d4-bb42-5c930be9f776 · outbound

This paper cites This model does not collapse, but only reaches a maximum IS of.

Large Scale GAN Training for High Fidelity Natural Image Synthesis This model does not collapse, but only reaches a maximum IS of

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T12:11:19.447378Z

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Observation 8ab9d9c9-75a0-4e92-92e7-fbe66f4117d5 · outbound

This paper cites Collapse occurs after 200000 iterations.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Collapse occurs after 200000 iterations

Reference 31

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Observation ff74625e-fd3e-429c-b38e-890bb6d456ae · outbound

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Large Scale GAN Training for High Fidelity Natural Image Synthesis Unresolved cited work

Reference 32

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This paper cites The consequence ofG being allowed to win the game is a complete breakdown of the training process, regardless of G’s conditioning or optimization settings.

Large Scale GAN Training for High Fidelity Natural Image Synthesis The consequence ofG being allowed to win the game is a complete breakdown of the training process, regardless of G’s conditioning or optimization settings

Reference 33

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This paper cites Increasing the margin beyond 3 results in unstable training similar to using the Wasserstein loss.

Large Scale GAN Training for High Fidelity Natural Image Synthesis Increasing the margin beyond 3 results in unstable training similar to using the Wasserstein loss

Reference 34

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Pith citing papers

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AGAN: Towards Automated Design of Generative Adversarial Networks cites this paper.

AGAN: Towards Automated Design of Generative Adversarial Networks Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 16

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Observation f556e833-58b6-4da5-9ddf-3274bb292e35 · inbound

Cellular State Transformations using Generative Adversarial Networks cites this paper.

Cellular State Transformations using Generative Adversarial Networks Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-25T12:36:57.734042Z

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Incremental Concept Learning via Online Generative Memory Recall cites this paper.

Incremental Concept Learning via Online Generative Memory Recall Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 44

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Observation a1fdb218-570c-44b6-9dd0-28c73b373999 · inbound

Copula & Marginal Flows: Disentangling the Marginal from its Joint cites this paper.

Copula & Marginal Flows: Disentangling the Marginal from its Joint Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 6

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Observation 90a4e73a-e606-495f-92b5-5613f69124d1 · inbound

Why we need an AI-resilient society cites this paper.

Why we need an AI-resilient society Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 13

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Observation cdb84435-2041-486a-826e-92619286ca79 · inbound

DiffWave: A Versatile Diffusion Model for Audio Synthesis cites this paper.

DiffWave: A Versatile Diffusion Model for Audio Synthesis Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 1

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Observation 7bdece6c-8acc-4ddf-baa8-16234e11e3b8 · inbound

Denoising Diffusion Implicit Models cites this paper.

Denoising Diffusion Implicit Models Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2

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Observation 34873d0e-cd27-4e15-ba0c-075db2a88913 · inbound

Scaling Laws for Transfer cites this paper.

Scaling Laws for Transfer Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 119

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Observation fe7eaf5d-8f55-4146-9020-f9e1497395fb · inbound

Improved Denoising Diffusion Probabilistic Models cites this paper.

Improved Denoising Diffusion Probabilistic Models Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 1

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Observation cb4471c5-4dce-48a8-9c8e-9a2868c6085b · inbound

VideoGPT: Video Generation using VQ-VAE and Transformers cites this paper.

VideoGPT: Video Generation using VQ-VAE and Transformers Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 5

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Observation 006b5276-f905-421e-9b32-41ccfc2129ec · inbound

Diffusion Models Beat GANs on Image Synthesis cites this paper.

Diffusion Models Beat GANs on Image Synthesis Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.483934Z

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Observation 5f90d774-0c55-4529-83e5-e8dae9f1fcc8 · inbound

A General Language Assistant as a Laboratory for Alignment cites this paper.

A General Language Assistant as a Laboratory for Alignment Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 161

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Observation 9543da2e-597e-4873-bcea-cdf280156f40 · inbound

GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models cites this paper.

GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.483934Z

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Observation 1d663c37-5dda-4812-b4e2-b36cffd8dfcf · inbound

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding cites this paper.

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.483934Z

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Observation 083052c7-030a-47b8-959e-2d0eb470f69f · inbound

Language Models (Mostly) Know What They Know cites this paper.

Language Models (Mostly) Know What They Know Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 238

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.483934Z

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Observation de00f250-b9cd-429c-ac64-7970daef4bf8 · inbound

Prompt-to-Prompt Image Editing with Cross Attention Control cites this paper.

Prompt-to-Prompt Image Editing with Cross Attention Control Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.483934Z

Source-reported events for the cited work

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Rectified Flow: A Marginal Preserving Approach to Optimal Transport cites this paper.

Rectified Flow: A Marginal Preserving Approach to Optimal Transport Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Reference 104

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Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation cites this paper.

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Observation ec9bfa6c-de8c-458e-ba4f-b0b0b22af699 · inbound

One Step Diffusion via Shortcut Models cites this paper.

One Step Diffusion via Shortcut Models Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 4

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Gravitational-Wave Parameter Estimation in non-Gaussian noise using Score-Based Likelihood Characterization cites this paper.

Gravitational-Wave Parameter Estimation in non-Gaussian noise using Score-Based Likelihood Characterization Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 21

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Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detection cites this paper.

Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detection Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 131

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RandAR: Decoder-only Autoregressive Visual Generation in Random Orders cites this paper.

RandAR: Decoder-only Autoregressive Visual Generation in Random Orders Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 1

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HunyuanVideo: A Systematic Framework For Large Video Generative Models cites this paper.

HunyuanVideo: A Systematic Framework For Large Video Generative Models Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 6

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Modeling Eye Gaze Velocity Trajectories using GANs with Spectral Loss for Enhanced Fidelity cites this paper.

Modeling Eye Gaze Velocity Trajectories using GANs with Spectral Loss for Enhanced Fidelity Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 20

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GMem: A Modular Approach for Ultra-Efficient Generative Models cites this paper.

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Reference 2022

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EvalGIM: A Library for Evaluating Generative Image Models cites this paper.

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Rapid Reconstruction of Extremely Accelerated Liver 4D MRI via Chained Iterative Refinement cites this paper.

Rapid Reconstruction of Extremely Accelerated Liver 4D MRI via Chained Iterative Refinement Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 34

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RapidNet: Multi-Level Dilated Convolution Based Mobile Backbone cites this paper.

RapidNet: Multi-Level Dilated Convolution Based Mobile Backbone Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Parallelized Autoregressive Visual Generation cites this paper.

Parallelized Autoregressive Visual Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 3

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FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching cites this paper.

FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Next Patch Prediction for Autoregressive Visual Generation cites this paper.

Next Patch Prediction for Autoregressive Visual Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 8

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Reference 34

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GeFL: Model-Agnostic Federated Learning with Generative Models cites this paper.

GeFL: Model-Agnostic Federated Learning with Generative Models Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 65

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Diverse Rare Sample Generation with Pretrained GANs cites this paper.

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Reference 6

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Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions cites this paper.

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Reference 84

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HFI: A unified framework for training-free detection and implicit watermarking of latent diffusion model generated images cites this paper.

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Reference 5

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Observation cb2225c2-97d1-469c-a5be-9efb1966412b · inbound

Navigating Image Restoration with VAR's Distribution Alignment Prior cites this paper.

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Taming Feed-forward Reconstruction Models as Latent Encoders for 3D Generative Models cites this paper.

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Reference 6

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Source-reported events for the cited work

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Improving Autoregressive Visual Generation with Cluster-Oriented Token Prediction cites this paper.

Improving Autoregressive Visual Generation with Cluster-Oriented Token Prediction Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 5

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Unavailable: canonical work link unavailable.

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Seeing Sound: Assembling Sounds from Visuals for Audio-to-Image Generation cites this paper.

Seeing Sound: Assembling Sounds from Visuals for Audio-to-Image Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2

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Source-reported events for the cited work

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The GAN is dead; long live the GAN! A Modern GAN Baseline cites this paper.

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Reference 3

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Yuan: Yielding Unblemished Aesthetics Through A Unified Network for Visual Imperfections Removal in Generated Images Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2

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Towards General Purpose Robots at Scale: Lifelong Learning and Learning to Use Memory cites this paper.

Towards General Purpose Robots at Scale: Lifelong Learning and Learning to Use Memory Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 14

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A New Formulation of Lipschitz Constrained With Functional Gradient Learning for GANs cites this paper.

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Reference 12

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Nested Annealed Training Scheme for Generative Adversarial Networks cites this paper.

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Reference 24

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Unavailable: canonical work link unavailable.

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CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling cites this paper.

CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 39

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Unavailable: canonical work link unavailable.

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Exploring Representation-Aligned Latent Space for Better Generation cites this paper.

Exploring Representation-Aligned Latent Space for Better Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2023

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Generative AI and Creative Work: Narratives, Values, and Impacts cites this paper.

Generative AI and Creative Work: Narratives, Values, and Impacts Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Generative Adversarial Networks Bridging Art and Machine Intelligence cites this paper.

Generative Adversarial Networks Bridging Art and Machine Intelligence Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 14

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

Beyond and Free from Diffusion: Invertible Guided Consistency Training Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2019

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Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation cites this paper.

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Reference 2000

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Revisiting the Auxiliary Data in Backdoor Purification cites this paper.

Revisiting the Auxiliary Data in Backdoor Purification Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing cites this paper.

Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Swin Transformer for Robust CGI Images Detection: Intra- and Inter-Dataset Analysis across Multiple Color Spaces cites this paper.

Swin Transformer for Robust CGI Images Detection: Intra- and Inter-Dataset Analysis across Multiple Color Spaces Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 13

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Beyond Equilibrium: Non-Equilibrium Foundations Should Underpin Generative Processes in Complex Dynamical Systems cites this paper.

Beyond Equilibrium: Non-Equilibrium Foundations Should Underpin Generative Processes in Complex Dynamical Systems Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 76

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Differentiable Solver Search for Fast Diffusion Sampling cites this paper.

Differentiable Solver Search for Fast Diffusion Sampling Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 1883

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A Cross Branch Fusion-Based Contrastive Learning Framework for Point Cloud Self-supervised Learning cites this paper.

A Cross Branch Fusion-Based Contrastive Learning Framework for Point Cloud Self-supervised Learning Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Common Inpainted Objects In-N-Out of Context cites this paper.

Common Inpainted Objects In-N-Out of Context Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 27

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Counterfactual Activation Editing for Post-hoc Prosody and Mispronunciation Correction in TTS Models cites this paper.

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Reference 39

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DFBench: Benchmarking Deepfake Image Detection Capability of Large Multimodal Models cites this paper.

DFBench: Benchmarking Deepfake Image Detection Capability of Large Multimodal Models Large Scale GAN Training for High Fidelity Natural Image Synthesis

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How Far Are We from Generating Missing Modalities with Foundation Models? cites this paper.

How Far Are We from Generating Missing Modalities with Foundation Models? Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 37

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Marrying Autoregressive Transformer and Diffusion with Multi-Reference Autoregression cites this paper.

Marrying Autoregressive Transformer and Diffusion with Multi-Reference Autoregression Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection cites this paper.

Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 16

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SpectralAR: Spectral Autoregressive Visual Generation cites this paper.

SpectralAR: Spectral Autoregressive Visual Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2a4bfa7-f8f7-42bb-814d-24e3ce805dda · inbound

Style Transfer: A Decade Survey cites this paper.

Style Transfer: A Decade Survey Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 138

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Source-reported events for the cited work

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Observation b0ff5968-3f05-4a5a-8685-5ef33f036e92 · inbound

SoK: Can Synthetic Images Replace Real Data? A Survey of Utility and Privacy of Synthetic Image Generation cites this paper.

SoK: Can Synthetic Images Replace Real Data? A Survey of Utility and Privacy of Synthetic Image Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 13

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Unavailable: canonical work link unavailable.

Observation b362542c-bee5-4e9a-bef4-c397731cac89 · inbound

Pay Less Attention to Deceptive Artifacts: Robust Detection of Compressed Deepfakes on Online Social Networks cites this paper.

Pay Less Attention to Deceptive Artifacts: Robust Detection of Compressed Deepfakes on Online Social Networks Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T22:52:28.410898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ab39326-3430-4716-a016-0925a67bc04f · inbound

Autoregressive Image Generation with Linear Complexity: A Spatial-Aware Decay Perspective cites this paper.

Autoregressive Image Generation with Linear Complexity: A Spatial-Aware Decay Perspective Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:48.529907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

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.

Observation fc5c5f9c-bb8d-4400-af77-026e324de654 · inbound

UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis cites this paper.

UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 35

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LAID: Lightweight AI-Generated Image Detection in Spatial and Spectral Domains cites this paper.

LAID: Lightweight AI-Generated Image Detection in Spatial and Spectral Domains Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 49

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CorrDetail: Visual Detail Enhanced Self-Correction for Face Forgery Detection cites this paper.

CorrDetail: Visual Detail Enhanced Self-Correction for Face Forgery Detection Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2024

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Diffusion Models for Time Series Forecasting: A Survey cites this paper.

Diffusion Models for Time Series Forecasting: A Survey Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 56

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Perceptual Classifiers: Detecting Generative Images using Perceptual Features cites this paper.

Perceptual Classifiers: Detecting Generative Images using Perceptual Features Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 6

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DACA-Net: A Degradation-Aware Conditional Diffusion Network for Underwater Image Enhancement cites this paper.

DACA-Net: A Degradation-Aware Conditional Diffusion Network for Underwater Image Enhancement Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 5

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PixNerd: Pixel Neural Field Diffusion cites this paper.

PixNerd: Pixel Neural Field Diffusion Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 4

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Leveraging Failed Samples: A Few-Shot and Training-Free Framework for Generalized Deepfake Detection cites this paper.

Leveraging Failed Samples: A Few-Shot and Training-Free Framework for Generalized Deepfake Detection Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 1

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Improving Diversity in Language Models: When Temperature Fails, Change the Loss cites this paper.

Improving Diversity in Language Models: When Temperature Fails, Change the Loss Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2000

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HumanGenesis: Agent-Based Geometric and Generative Modeling for Synthetic Human Dynamics cites this paper.

HumanGenesis: Agent-Based Geometric and Generative Modeling for Synthetic Human Dynamics Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 3

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FBI: Learning Dexterous In-hand Manipulation with Dynamic Visuotactile Shortcut Policy cites this paper.

FBI: Learning Dexterous In-hand Manipulation with Dynamic Visuotactile Shortcut Policy Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 5

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Scaling Group Inference for Diverse and High-Quality Generation cites this paper.

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Reference 49

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Reusing Computation in Text-to-Image Diffusion for Efficient Generation of Image Sets cites this paper.

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Reference 4

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Transition Models: Rethinking the Generative Learning Objective Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 8

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Scalable Training for Vector-Quantized Networks with 100% Codebook Utilization cites this paper.

Scalable Training for Vector-Quantized Networks with 100% Codebook Utilization Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 5

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Overclocking Electrostatic Generative Models cites this paper.

Overclocking Electrostatic Generative Models Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 1

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Less is More: Recursive Reasoning with Tiny Networks cites this paper.

Less is More: Recursive Reasoning with Tiny Networks Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 2

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Observation 1a3f05f8-1d4a-4865-bf52-35b27eb85039 · inbound

IAR2: Improving Autoregressive Visual Generation with Semantic-Detail Associated Token Prediction cites this paper.

IAR2: Improving Autoregressive Visual Generation with Semantic-Detail Associated Token Prediction Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 45

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Unavailable: canonical work link unavailable.

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How Noise Benefits AI-generated Image Detection cites this paper.

How Noise Benefits AI-generated Image Detection Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance cites this paper.

Hybrid Synthetic Data Generation with Domain Randomization Enables Zero-Shot Vision-Based Part Inspection Under Extreme Class Imbalance Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 36

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Unavailable: canonical work link unavailable.

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SketchAssist: A Practical Assistant for Semantic Edits and Precise Local Redrawing cites this paper.

SketchAssist: A Practical Assistant for Semantic Edits and Precise Local Redrawing Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T16:18:21.808063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Mirai: Autoregressive Visual Generation Needs Foresight cites this paper.

Mirai: Autoregressive Visual Generation Needs Foresight Large Scale GAN Training for High Fidelity Natural Image Synthesis

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Resolution: verified exact; local_arxiv, observed 2026-05-16T12:17:52.075726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d1585e1e-87c5-4c20-867f-2b16bbd9f2e2 · inbound

MPDiT: Multi-Patch Global-to-Local Transformer Architecture For Efficient Flow Matching and Diffusion Model cites this paper.

MPDiT: Multi-Patch Global-to-Local Transformer Architecture For Efficient Flow Matching and Diffusion Model Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-14T23:48:19.343485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7f21afb9-05b7-4b6c-b60e-a5ef679b1cd4 · inbound

SurFITR: A Dataset for Surveillance Image Forgery Detection and Localisation cites this paper.

SurFITR: A Dataset for Surveillance Image Forgery Detection and Localisation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.483934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6aa32168-e7cf-43c9-9d3f-3603b04674b0 · inbound

Multimodal Large Language Models for Multi-Subject In-Context Image Generation cites this paper.

Multimodal Large Language Models for Multi-Subject In-Context Image Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T12:11:19.483934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 583804ea-7f4d-43f9-8597-f93bdd82cb04 · inbound

ELT: Elastic Looped Transformers for Visual Generation cites this paper.

ELT: Elastic Looped Transformers for Visual Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.483934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3188a568-0b40-4669-ba66-ed7ab625fe76 · inbound

ELT: Elastic Looped Transformers for Visual Generation cites this paper.

ELT: Elastic Looped Transformers for Visual Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T16:35:03.108988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cf3d7f4-d770-4fd5-a61d-80c2d3cf71f4 · inbound

Frequency-Aware Flow Matching for High-Quality Image Generation cites this paper.

Frequency-Aware Flow Matching for High-Quality Image Generation Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:11:19.483934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.