Paper Citation Record · LEDGER

Text-to-Image GAN with Pretrained Representations

As of 11 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2501.00116.

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

pith.paper-citation-record.v1
2501.00116 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:05:13.761523Z

measured 40 of 40 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

verified exact1
verified fuzzy28
unresolved11
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 193a1ede-4da1-4ea5-852f-9ba0e14348e4 · outbound

This paper cites eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers.

Text-to-Image GAN with Pretrained Representations eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers

Reference 1

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Source-reported events for the cited work

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Observation 5d456aaf-d281-4b77-8e77-dc55a52f9dde · outbound

This paper cites Cogview: Mastering text-to-image generation via transformers.

Text-to-Image GAN with Pretrained Representations Cogview: Mastering text-to-image generation via transformers

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.231518Z

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Observation 755e8e8f-cfd6-43d0-ae4e-52259e0daed7 · outbound

This paper cites Cogview2: Faster and better text-to-image generation via hierarchical transformers.

Text-to-Image GAN with Pretrained Representations Cogview2: Faster and better text-to-image generation via hierarchical transformers

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.220351Z

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Observation 138f4b5e-0e82-4c8d-b456-2ead615cdb8c · outbound

This paper cites Vector quantized diffusion model for text- to-image synthesis.

Text-to-Image GAN with Pretrained Representations Vector quantized diffusion model for text- to-image synthesis

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.208426Z

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Observation 4283bf23-1304-4954-b8cb-f501e2c38a85 · outbound

This paper cites Visual Attention Network.

Text-to-Image GAN with Pretrained Representations Visual Attention Network

Reference 8

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Source-reported events for the cited work

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Observation 4180485e-df93-4ffe-95ec-5bc67eb88185 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Text-to-Image GAN with Pretrained Representations Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.196159Z

Source-reported events for the cited work

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Observation 6adcb0ee-6916-48db-90d3-cf0f25990719 · outbound

This paper cites Adam: A method for stochastic optimization.

Text-to-Image GAN with Pretrained Representations Adam: A method for stochastic optimization

Reference 11

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Source-reported events for the cited work

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Observation 670a81fb-25be-42cc-8d42-26de063cc77d · outbound

This paper cites Text to image generation with semantic-spatial aware gan.

Text-to-Image GAN with Pretrained Representations Text to image generation with semantic-spatial aware gan

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.136493Z

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Observation 7a72d765-df33-4f19-89df-a7b5cf3df2cd · outbound

This paper cites Microsoft coco: Com- mon objects in context.

Text-to-Image GAN with Pretrained Representations Microsoft coco: Com- mon objects in context

Reference 15

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Source-reported events for the cited work

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Observation cf9bca88-e215-4835-a196-c08c76a927df · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Text-to-Image GAN with Pretrained Representations Swin transformer: Hierarchical vision transformer using shifted windows

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.112384Z

Source-reported events for the cited work

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Observation 61086c16-2f01-442f-9a8c-bbd9a29ba7bd · outbound

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

Text-to-Image GAN with Pretrained Representations GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 17

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Source-reported events for the cited work

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Observation 9e1c88b9-2b97-4bad-8f00-6f950dfc9e17 · outbound

This paper cites Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.

Text-to-Image GAN with Pretrained Representations Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

Reference 18

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Source-reported events for the cited work

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Observation 2e24ac50-ca07-4e22-aecc-ab214da02315 · outbound

This paper cites Learning transferable visual models from nat- ural language supervision.

Text-to-Image GAN with Pretrained Representations Learning transferable visual models from nat- ural language supervision

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.100268Z

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 07aee608-a9a4-4b0d-9dd6-9e0b8915fe49 · outbound

This paper cites Zero-shot text-to-image generation.

Text-to-Image GAN with Pretrained Representations Zero-shot text-to-image generation

Reference 20

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Source-reported events for the cited work

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Observation abec9f14-4cd9-454d-b2a2-5f9d0feb1c69 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Text-to-Image GAN with Pretrained Representations Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 21

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Observation 5167e705-b356-46b3-a7f5-6a4a06addcb7 · outbound

This paper cites Dae- gan: Dynamic aspect-aware gan for text-to-image synthe- sis.

Text-to-Image GAN with Pretrained Representations Dae- gan: Dynamic aspect-aware gan for text-to-image synthe- sis

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.068233Z

Source-reported events for the cited work

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Observation 02136172-77c0-451e-a7f9-00e0e35df7be · outbound

This paper cites Improved techniques for training gans.

Text-to-Image GAN with Pretrained Representations Improved techniques for training gans

Reference 24

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Source-reported events for the cited work

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Observation 1091660b-ad27-49df-beed-6b7fb52e5371 · outbound

This paper cites Projected gans converge faster.

Text-to-Image GAN with Pretrained Representations Projected gans converge faster

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.043885Z

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 b0ea2a9a-1d93-4b69-a8ff-c681fcd12386 · outbound

This paper cites StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis.

Text-to-Image GAN with Pretrained Representations StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis

Reference 26

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Observation 814d71cb-2a3d-4482-8c26-652d81d3dce6 · outbound

This paper cites A u-net based discriminator for generative adversarial networks.

Text-to-Image GAN with Pretrained Representations A u-net based discriminator for generative adversarial networks

Reference 27

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Observation f97a4185-e806-4422-87a1-9ff52377bc3d · outbound

This paper cites Rethinking the inception architecture for computer vision.

Text-to-Image GAN with Pretrained Representations Rethinking the inception architecture for computer vision

Reference 29

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Observation 6dcf9b75-964c-4cd8-8e0f-6bb1b6e8e465 · outbound

This paper cites DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis.

Text-to-Image GAN with Pretrained Representations DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis

Reference 30

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Source-reported events for the cited work

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Observation 24a7397c-6fb6-4913-b5f0-31f89178565a · outbound

This paper cites Df-gan: A sim- ple and effective baseline for text-to-image synthesis.

Text-to-Image GAN with Pretrained Representations Df-gan: A sim- ple and effective baseline for text-to-image synthesis

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:13.993022Z

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Observation 110197b5-837f-4f0e-b834-28330ad1f918 · outbound

This paper cites Galip: Generative adversarial clips for text-to-image synthesis.

Text-to-Image GAN with Pretrained Representations Galip: Generative adversarial clips for text-to-image synthesis

Reference 32

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Observation 4d09ad61-9cd6-4287-b466-1b90c5c44dea · outbound

This paper cites The caltech- ucsd birds-200-2011 dataset.

Text-to-Image GAN with Pretrained Representations The caltech- ucsd birds-200-2011 dataset

Reference 33

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Observation 5f838876-fc7a-4165-a8d3-daadcbbee38b · outbound

This paper cites Scaling Autoregressive Models for Content-Rich Text-to-Image Generation.

Text-to-Image GAN with Pretrained Representations Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Reference 36

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Observation bcf619f7-0b44-44b7-acf6-ff1b5dfe99ef · outbound

This paper cites Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial net- works.

Text-to-Image GAN with Pretrained Representations Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial net- works

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:13.947543Z

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Observation 128167e9-246d-4cd2-83e9-605abd4a87a8 · outbound

This paper cites Cross-modal contrastive learning for text-to-image generation.

Text-to-Image GAN with Pretrained Representations Cross-modal contrastive learning for text-to-image generation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:13.935491Z

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Observation 9d200783-fe63-4da7-aa6e-a234037c3619 · outbound

This paper cites Towards language-free training for text-to-image generation.

Text-to-Image GAN with Pretrained Representations Towards language-free training for text-to-image generation

Reference 39

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Observation 41e3ad65-0747-4ae3-bfac-2a1f012fa4cf · outbound

This paper cites Dm-gan: Dynamic memory generative adversar- ial networks for text-to-image synthesis.

Text-to-Image GAN with Pretrained Representations Dm-gan: Dynamic memory generative adversar- ial networks for text-to-image synthesis

Reference 40

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Observation 5a8bd889-0829-4eb2-b797-577fe4322d3f · outbound

This paper cites Attngan: Fine-grained text to image gener- ation with attentional generative adversarial networks.

Text-to-Image GAN with Pretrained Representations Attngan: Fine-grained text to image gener- ation with attentional generative adversarial networks

Reference 2011

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:13.960113Z

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Observation bd425ebe-73ba-4dea-8fc3-f7c2b51c572c · outbound

This paper cites Ensembling off-the-shelf models for gan training.

Text-to-Image GAN with Pretrained Representations Ensembling off-the-shelf models for gan training

Reference 2014

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Observation 3eba33bc-3ad8-428b-b139-53a5b3281c0e · outbound

This paper cites Kingma and Max Welling.

Text-to-Image GAN with Pretrained Representations Kingma and Max Welling

Reference 2015

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Source-reported events for the cited work

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Observation 2e2f5d08-944c-4fda-878c-c240ffd4adc6 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Text-to-Image GAN with Pretrained Representations High-resolution image synthesis with latent diffusion models

Reference 2016

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Source-reported events for the cited work

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Observation 4527565c-84a1-4de4-b384-a9269c9702ca · outbound

This paper cites Scaling up gans for text-to-image syn- thesis.

Text-to-Image GAN with Pretrained Representations Scaling up gans for text-to-image syn- thesis

Reference 2017

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Observation 0070fa8d-8bef-4c3f-af4b-52811b3ef965 · outbound

This paper cites Recurrent Affine Transformation for Text-to-image Synthesis.

Text-to-Image GAN with Pretrained Representations Recurrent Affine Transformation for Text-to-image Synthesis

Reference 2018

Resolution: verified exact; local_arxiv, observed 2026-08-10T23:05:13.812195Z

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Observation 0056adfe-e962-4abe-8ef7-ad7578c15ae1 · outbound

This paper cites Very deep convolutional networks for large-scale image recognition.

Text-to-Image GAN with Pretrained Representations Very deep convolutional networks for large-scale image recognition

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.019723Z

Source-reported events for the cited work

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Observation c4d75ffb-116f-45f4-8bfa-3b25bbf55808 · outbound

This paper cites Muse: Text-To-Image Generation via Masked Generative Transformers.

Text-to-Image GAN with Pretrained Representations Muse: Text-To-Image Generation via Masked Generative Transformers

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-10T23:05:13.618967Z

Source-reported events for the cited work

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Observation f9e7bacb-afcb-4f1c-8332-407e25eaf35a · outbound

This paper cites Emerging properties in self-supervised vi- sion transformers.

Text-to-Image GAN with Pretrained Representations Emerging properties in self-supervised vi- sion transformers

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.254006Z

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 e88b32fd-2844-4386-a6c3-8a9a7621ba4c · outbound

This paper cites Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts.

Text-to-Image GAN with Pretrained Representations Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:14.242531Z

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.

Pith citing papers

No inbound Pith citation observations are available.