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Paper Citation Record · LEDGER

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting

As of 20 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2506.12530.

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

pith.paper-citation-record.v1
2506.12530 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:52:25.256523Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

31 of 31 outbound references displayed

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  • verified fuzzy12
  • unresolved18
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 05d98ec5-c607-4625-bc4f-63e5b2025282 · outbound

This paper cites Blended latent diffusion.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Blended latent diffusion

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0eb6e711-f8dd-4c79-841f-674a7c6ad542 · outbound

This paper cites Generative adversarial nets.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Generative adversarial nets

Reference 2

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Unavailable: canonical work link unavailable.

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Observation 3b700e14-e998-46cb-9de0-6449314aeec0 · outbound

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

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 3

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no resolver link, observed 2026-08-07T00:52:25.167368Z

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Unavailable: canonical work link unavailable.

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Observation 94ad1053-d7b0-4ed0-934a-bc544039ae34 · outbound

This paper cites Denoising dif- fusion probabilistic models.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Denoising dif- fusion probabilistic models

Reference 4

Resolution
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no resolver link, observed 2026-08-07T00:52:25.170313Z

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Unavailable: canonical work link unavailable.

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Observation 9e1b6e55-f95e-4742-9f1e-b08ae385ccff · outbound

This paper cites Image Fine-grained Inpainting.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Image Fine-grained Inpainting

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:52:25.375867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d24ea808-072c-41d9-baf6-ea3182613ca2 · outbound

This paper cites BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 492d4c2c-11a8-4f1e-b725-d215d95e388f · outbound

This paper cites Analyzing and improv- ing the image quality of stylegan.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Analyzing and improv- ing the image quality of stylegan

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f4e5994f-60b8-4c63-9de1-63f867e1c799 · outbound

This paper cites Auto-Encoding Variational Bayes.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Auto-Encoding Variational Bayes

Reference 8

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unresolved
no resolver link, observed 2026-08-07T00:52:25.184064Z

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Unavailable: canonical work link unavailable.

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Observation 0b40cb71-c1ea-46a0-a9bc-a086905b5590 · outbound

This paper cites Rethinking image inpainting via a mutual encoder- decoder with feature equalizations.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Rethinking image inpainting via a mutual encoder- decoder with feature equalizations

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:52:25.528837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 98925185-54d5-4e05-9ab0-aedb6ea5ac67 · outbound

This paper cites Repaint: Inpainting using denoising diffusion probabilistic models.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Repaint: Inpainting using denoising diffusion probabilistic models

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e0c466c1-f06b-43c8-bb46-25a7226102d2 · outbound

This paper cites HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models

Reference 11

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Observation f60afe8e-5e49-49b8-bdbf-8df40f60ec19 · outbound

This paper cites Aim 2020 challenge on image extreme inpainting.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Aim 2020 challenge on image extreme inpainting

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:52:25.511564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 25e340f5-d35d-4698-ae86-06f7b09dd943 · outbound

This paper cites Scalable diffusion models with transformers.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Scalable diffusion models with transformers

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:52:25.198621Z digest=sha256:18d8f48bdd55f2a67de5701ceee77983aeaec86c70eec96a813374247a7ddf69

Observation 6fe6e30a-830b-4d2e-85d6-c7f54f3add0e · outbound

This paper cites Gen- erating diverse structure for image inpainting with hierar- chical vq-vae.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Gen- erating diverse structure for image inpainting with hierar- chical vq-vae

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:52:25.496009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0c2b8498-b63e-45e5-8c70-41d31f85396a · outbound

This paper cites U2-net: Go- ing deeper with nested u-structure for salient object detec- tion.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting U2-net: Go- ing deeper with nested u-structure for salient object detec- tion

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:52:25.485763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f0620f84-e824-4921-84a2-22c286b0d2d2 · outbound

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

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting High-resolution image synthesis with latent diffusion models

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:52:25.474758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 193bb74e-5743-4cb7-88ef-eae8a151a1f1 · outbound

This paper cites Palette: Image-to-image diffusion models.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Palette: Image-to-image diffusion models

Reference 17

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no resolver link, observed 2026-08-07T00:52:25.209995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ab1832dc-ae52-4ea7-9b49-4984ff211a8a · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Progressive Distillation for Fast Sampling of Diffusion Models

Reference 18

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Unavailable: canonical work link unavailable.

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Observation c72f3752-80dd-45ed-8fdb-97cc2c9bec1f · outbound

This paper cites Mi-gan: A simple baseline for image in- painting on mobile devices.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Mi-gan: A simple baseline for image in- painting on mobile devices

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:52:25.457977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 1949b3ff-6fdf-49cf-adcd-779edf9109cd · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation debbbe94-d533-4b8f-9fe9-19add02af3ba · outbound

This paper cites Denoising Diffusion Implicit Models.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Denoising Diffusion Implicit Models

Reference 21

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Unavailable: canonical work link unavailable.

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Observation 1e2f78ea-7452-48b0-8957-80b8de039ea6 · outbound

This paper cites Resolution-robust large mask inpainting with fourier convolutions.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Resolution-robust large mask inpainting with fourier convolutions

Reference 22

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Observation 811b3704-3ffc-42f7-bdbe-cb4a94eb96a2 · outbound

This paper cites Smartbrush: Text and shape guided object inpainting with diffusion model.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Smartbrush: Text and shape guided object inpainting with diffusion model

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 269daa39-f8ae-448a-8c41-3693def1c585 · outbound

This paper cites Image completion with heterogeneously filtered spectral hints.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Image completion with heterogeneously filtered spectral hints

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-07T00:52:25.424268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T00:52:25.232734Z digest=sha256:efdeb8dcccb77f4efb3b69509713f7b0fb958cf622d10782d81339fb5ecf7efd

Observation c877396f-cc74-4fb3-8c72-a666c5725be1 · outbound

This paper cites A review of image in- painting methods based on deep learning.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting A review of image in- painting methods based on deep learning

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-07T00:52:25.414369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T00:52:25.235677Z digest=sha256:b91868b8be7f5e1ca823d854d82fd38473770bf3bf229d2b958e5c7635a5b432

Observation 8df921bb-1c3c-4bef-903c-e35aba7c4e32 · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applications.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Diffusion models: A comprehensive survey of methods and applications

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 650f014e-6e57-41d0-a2ef-e4b0b239a38d · outbound

This paper cites Uctgan: Diverse image inpainting based on unsupervised cross-space translation.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Uctgan: Diverse image inpainting based on unsupervised cross-space translation

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:52:25.397815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 570d7175-3de4-4dcd-b43c-3be41a193a1f · outbound

This paper cites Large Scale Image Completion via Co-Modulated Generative Adversarial Networks.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Large Scale Image Completion via Co-Modulated Generative Adversarial Networks

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:52:25.245397Z digest=sha256:4c5da0d3d329c3f5b434447adc73fde03d32c3312ed51bd7a2fe825df0b0e598

Observation 6da197a1-9656-4677-b1e5-4c3b17615707 · outbound

This paper cites Pluralistic image completion.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting Pluralistic image completion

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-07T00:52:25.386768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T00:52:25.249227Z digest=sha256:bf6e3bef9c9cf5169f3840e1a433fefc05da5a1d9ea38acfefc27d6fdd914260

Observation 09feb853-38e3-4e35-b788-50f9f5768929 · outbound

This paper cites CM-GAN: Image Inpainting with Cascaded Modulation GAN and Object-Aware Training.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting CM-GAN: Image Inpainting with Cascaded Modulation GAN and Object-Aware Training

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bb6829df-83af-491e-83ac-482fa98888fb · outbound

This paper cites A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting.

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting

Reference 31

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Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.