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Paper Citation Record · LEDGER

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data

As of 4 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 1 inbound Pith citation observation for arXiv:2603.03239.

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

pith.paper-citation-record.v1
2603.03239 v3

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

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measured 71 of 71 standing notices

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T15:15:41.382826Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

70 of 70 outbound references displayed

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External citation measurements

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Outbound references

Observation 68a238ec-6745-4476-b7b3-2cef336d2133 · outbound

This paper cites SegDiff: Image Segmentation with Diffusion Probabilistic Models.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data SegDiff: Image Segmentation with Diffusion Probabilistic Models

Reference 1

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Observation cf11f098-af7d-4602-9c83-32b64788829e · outbound

This paper cites Efficient remote sensing image super- resolution via lightweight diffusion models.IEEE Geoscience and Remote Sensing Letters.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Efficient remote sensing image super- resolution via lightweight diffusion models.IEEE Geoscience and Remote Sensing Letters

Reference 2

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Observation f701fbeb-d3f5-4d0d-a1fb-3e2a8e8642dc · outbound

This paper cites Joint-embedding vs reconstruction: Provable benefits of latent space prediction for self-supervised learning.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Joint-embedding vs reconstruction: Provable benefits of latent space prediction for self-supervised learning

Reference 3

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Observation 4c5cc118-f22e-4012-aff6-7aa102db24d9 · outbound

This paper cites OmniSat: Self-supervised modal- ity fusion for Earth observation.ECCV.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data OmniSat: Self-supervised modal- ity fusion for Earth observation.ECCV

Reference 4

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Observation dbd0eb4e-2f49-4832-af4b-c0a40302601f · outbound

This paper cites DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detection.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detection

Reference 5

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Observation 523a9cd4-492b-4b9e-b360-8cd710adafa5 · outbound

This paper cites All are worth words: A vit backbone for diffusion models.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data All are worth words: A vit backbone for diffusion models

Reference 6

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Observation 9c9146f5-ba70-4f03-9059-a02673db956a · outbound

This paper cites One transformer fits all distributions in multi- modal diffusion at scale.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data One transformer fits all distributions in multi- modal diffusion at scale

Reference 7

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Observation c5aa90fb-bf3a-46ef-87e7-64bbb5c143ef · outbound

This paper cites Brown, Michal R.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Brown, Michal R

Reference 8

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Observation 5ae2f5da-44f1-4470-bded-12fc2fc90200 · outbound

This paper cites Terrafm: A scalable foundation model for unified multisensor earth observation.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Terrafm: A scalable foundation model for unified multisensor earth observation

Reference 9

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Observation ce8bd981-e17b-4275-870c-cacb3ad4cec8 · outbound

This paper cites Diffusion models beat GANs on image synthesis.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Diffusion models beat GANs on image synthesis

Reference 10

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Observation d0397bdd-3d33-4f74-9586-faa7fae82461 · outbound

This paper cites Building bridges across spa- tial and temporal resolutions: Reference-based super- resolution via change priors and conditional diffusion model.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Building bridges across spa- tial and temporal resolutions: Reference-based super- resolution via change priors and conditional diffusion model

Reference 11

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Observation be2d18cf-ed9f-4a06-8da4-710e5ae39397 · outbound

This paper cites Remote sensing image super-resolution via enhanced back-projection networks.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Remote sensing image super-resolution via enhanced back-projection networks

Reference 12

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Observation a1793644-a38b-4ced-8c6f-0ffa3e3025f6 · outbound

This paper cites Cop-gen-beta: Unified generative modelling of copernicus imagery thumbnails.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Cop-gen-beta: Unified generative modelling of copernicus imagery thumbnails

Reference 13

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Observation c9ab86d4-abb7-4c1d-8309-d02073115ba4 · outbound

This paper cites Taming transformers for high-resolution image syn- thesis.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Taming transformers for high-resolution image syn- thesis

Reference 14

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Source-reported events for the cited work

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Observation d897182a-02c9-4157-a06c-2d5521619e50 · outbound

This paper cites Prithvi-eo-2.0: A versatile multi-temporal foundation model for earth observation applications.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Prithvi-eo-2.0: A versatile multi-temporal foundation model for earth observation applications

Reference 15

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Observation 8404d7d8-f41d-4c17-b3f1-e6bab005226d · outbound

This paper cites Copernicus: Europes eyes on Earth.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Copernicus: Europes eyes on Earth

Reference 16

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Observation aaaf94bb-2ff6-4ca1-ae63-12f76f3eff24 · outbound

This paper cites Coomes, Anil Madhavapeddy, Andrew Blake, and Srinivasan Keshav.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Coomes, Anil Madhavapeddy, Andrew Blake, and Srinivasan Keshav

Reference 17

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Observation 540e21d6-90d8-4cd5-bbf0-7ecf67f119ee · outbound

This paper cites Major tom: Expandable datasets for earth observation.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Major tom: Expandable datasets for earth observation

Reference 18

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Observation 52daa8e4-d879-4fe4-b433-5a13b96ed090 · outbound

This paper cites Masked diffusion transformer is a strong image synthesizer.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Masked diffusion transformer is a strong image synthesizer

Reference 19

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Observation cb5cbd56-39a6-41e3-b9ea-4208130ad1f2 · outbound

This paper cites Generative adversar- ial nets.Advances in Neural Information Processing Systems, 27.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Generative adversar- ial nets.Advances in Neural Information Processing Systems, 27

Reference 20

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Observation 6ef81d01-52f5-42a4-9b37-141c4730bcc1 · outbound

This paper cites TDiffDe: A Truncated Diffusion Model for Remote Sensing Hyperspectral Image Denoising.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data TDiffDe: A Truncated Diffusion Model for Remote Sensing Hyperspectral Image Denoising

Reference 21

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Observation 62589fe2-88e4-4b26-ba56-d6d240a4429d · outbound

This paper cites Olmoearth: Stable latent image model- ing for multimodal earth observation.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Olmoearth: Stable latent image model- ing for multimodal earth observation

Reference 22

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Observation 8b974d00-959d-43d1-80b6-4ad659a16e9b · outbound

This paper cites Denoising diffusion probabilistic models.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Denoising diffusion probabilistic models

Reference 23

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Observation f57c0121-92e9-49ad-a466-98f9c6d5ed23 · outbound

This paper cites TerraMind: Large-Scale Generative Multimodality for Earth Observation.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data TerraMind: Large-Scale Generative Multimodality for Earth Observation

Reference 24

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Observation b2060bb0-9cde-427d-96c4-38622e992194 · outbound

This paper cites Siamese meets diffusion network: Smdnet for en- hanced change detection in high-resolution rs imagery.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Siamese meets diffusion network: Smdnet for en- hanced change detection in high-resolution rs imagery

Reference 25

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Observation 63af341e-ca69-47f3-b4b7-017da21036e5 · outbound

This paper cites Can Generative Geospatial Diffusion Models Excel as Discriminative Geospatial Foundation Models?.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Can Generative Geospatial Diffusion Models Excel as Discriminative Geospatial Foundation Models?

Reference 26

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Observation 876e8afe-2770-41e6-b500-e9713a795169 · outbound

This paper cites Hya- gan: remote sensing image cloud removal based on hy- brid attention generation adversarial network.Interna- tional Journal of Remote Sensing, 45(6):1755–1773.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Hya- gan: remote sensing image cloud removal based on hy- brid attention generation adversarial network.Interna- tional Journal of Remote Sensing, 45(6):1755–1773

Reference 27

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Observation b09bde4c-e93d-4c04-b35b-efc054639b7f · outbound

This paper cites Denoising diffusion probabilistic feature-based network for cloud removal in sentinel-2 imagery.Remote Sensing, 15(9):2217.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Denoising diffusion probabilistic feature-based network for cloud removal in sentinel-2 imagery.Remote Sensing, 15(9):2217

Reference 28

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Observation 18c6afef-b22c-4e3b-90eb-b0b99df17566 · outbound

This paper cites Analyz- ing and improving the image quality of StyleGAN.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Analyz- ing and improving the image quality of StyleGAN

Reference 29

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Source-reported events for the cited work

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Observation 3726d8d7-63a1-4a41-91ea-9abd13d3b292 · outbound

This paper cites DiffusionSat: A Generative Foundation Model for Satellite Imagery.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data DiffusionSat: A Generative Foundation Model for Satellite Imagery

Reference 30

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Observation f5782db0-c6fa-4d82-886f-9634587f277d · outbound

This paper cites Multi-class segmentation from aerial views using recursive noise diffusion.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Multi-class segmentation from aerial views using recursive noise diffusion

Reference 31

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation 26202405-69bc-46e5-8ec8-1a61feccd4be · outbound

This paper cites Improved precision and recall metric for assessing generative models.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Improved precision and recall metric for assessing generative models

Reference 32

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation 9bc77545-5ecb-4564-926a-ba88f190dd38 · outbound

This paper cites Lawrence, Victoria L.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Lawrence, Victoria L

Reference 33

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verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.805976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:1c076c9af51431e15554e5f609148ef47a0210afa42f686b38cf03640519e6db

Observation 8e6ad156-3e87-498c-8908-70664ce9e807 · outbound

This paper cites Detecting out-of-distribution earth observation images with dif- fusion models.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Detecting out-of-distribution earth observation images with dif- fusion models

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.819006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:ac5f5bc7fdc324114ab107c7b96ec9715fdf44a797040bd0198a09e515f01a25

Observation 7839967a-9cfb-41e9-b179-02f1519c5e10 · outbound

This paper cites Mdfl: Multi-domain diffusion-driven feature learn- ing.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Mdfl: Multi-domain diffusion-driven feature learn- ing

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.864629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:8ce9137324de0db5682002334dc396a8db5fbe737d6a3b8fa73b64f647ad8f10

Observation 12ca3a4d-c4fb-44eb-a1bb-428617bb6281 · outbound

This paper cites A generative adversar- ial network for pixel-scale lunar dem generation from high-resolution monocular imagery and low-resolution dem.Remote Sensing, 14(21):5420.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data A generative adversar- ial network for pixel-scale lunar dem generation from high-resolution monocular imagery and low-resolution dem.Remote Sensing, 14(21):5420

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.755589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:2d99ddb56521594a1310ab30428cd931aaa8152d87aea5ee6cce56a33939274f

Observation 07509b75-210d-48f0-aa3f-c242c12ecc6b · outbound

This paper cites Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectives.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectives

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-15T16:40:10.425511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:20864829e86ff5ee06fdfb4483deb09f1e6b43e2fd1fa695b63e32510914df87

Observation bf843dfc-d490-4fcd-83ba-1fc5327e7e27 · outbound

This paper cites Revisiting clas- sifier two-sample tests.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Revisiting clas- sifier two-sample tests

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.860790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:79896705d534f487abfe1023231f89967b330c34269221c7a1290eb31a9ef8b7

Observation ffb479d3-66ac-4fd1-a934-36778b849c6f · outbound

This paper cites Pan-gan: An unsupervised pan-sharpening method for remote sensing image fu- sion.Information Fusion, 62:110–120.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Pan-gan: An unsupervised pan-sharpening method for remote sensing image fu- sion.Information Fusion, 62:110–120

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.852701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:998ff773dfc20c46731e87e1f7cb13c72361d4f1fed03a56babe894dec24204b

Observation a7367a92-7318-4964-9252-52ad342156f8 · outbound

This paper cites Cloud removal in sentinel-2 imagery using a deep residual neural network and sar-optical data fusion.ISPRS Journal of Photogrammetry and Remote Sensing, 166:333–346.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Cloud removal in sentinel-2 imagery using a deep residual neural network and sar-optical data fusion.ISPRS Journal of Photogrammetry and Remote Sensing, 166:333–346

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.790015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:6dab214d3c045b73b88af08a5e0a4791bc164254771fc4e1967b4f58a03cb7c6

Observation 18865222-4a91-42e6-a9ae-540de9fa6a61 · outbound

This paper cites Mmearth: Exploring multi-modal pretext tasks for geospatial representation learning.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Mmearth: Exploring multi-modal pretext tasks for geospatial representation learning

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.856969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:9496b84bf1a5131d9dd5ef307fcdb94bf5c1e964d3dbc6f73051eaf904f53a54

Observation 423d0f75-c721-4291-a611-1e5c5439062b · outbound

This paper cites Hir-diff: Unsu- pervised hyperspectral image restoration via improved diffusion models.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Hir-diff: Unsu- pervised hyperspectral image restoration via improved diffusion models

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.848174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:2d28ed66450117cdbe1395afef7af40b4eafb05011dc9ea10481fd32b44033f4

Observation 2a903e96-f14c-4171-9fae-c19abad8ad33 · outbound

This paper cites Correction of banding errors in satellite images with generative adversarial networks (gan).IEEE Access, 11:51960–51970.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Correction of banding errors in satellite images with generative adversarial networks (gan).IEEE Access, 11:51960–51970

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.743572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:d47506e1b1a183a9dc4931b7f6df095bb25ddba12f730852fd604c7e639e1137

Observation 5edf54bf-4a41-4faa-8c4a-91dbb25369a8 · outbound

This paper cites Scalable diffu- sion models with transformers.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Scalable diffu- sion models with transformers

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.717942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:92240a86e487b50921e4740669241a46594341897238ad82d599890f443a5662

Observation f5727fa4-78cb-4c99-afd1-154bcea3ed07 · outbound

This paper cites Lds2ae: Local diffusion shared-specific autoen- coder for multimodal remote sensing image classifi- cation with arbitrary missing modalities.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Lds2ae: Local diffusion shared-specific autoen- coder for multimodal remote sensing image classifi- cation with arbitrary missing modalities

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.811484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:3d9ed05236a09c4e0e207f5e95a72dddbb3dc9707ae6131cb23c1d5a68bd8cdc

Observation 26ae40c5-ed5c-49a9-92e3-2c4e4c4c7c0e · outbound

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

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Zero-shot text-to-image generation

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.747893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:388e3469d7346c27c2f8bcfdacd1d98632af165c472715c08793790f7e59e9b9

Observation 55e13bbc-8d7e-41ba-bba5-7f6ff1c24940 · outbound

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

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data High- resolution image synthesis with latent diffusion mod- els

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.759165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:93bf6d88c4990da61dc1e8e071e8bd517c0c3b56954cc1a6a59a786729986412

Observation 1e80395e-7912-4925-9cda-9b5f3db88778 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.International Conference on Medical Image Computing and Computer-Assisted Interven- tion.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data U-net: Convolutional networks for biomedical image segmentation.International Conference on Medical Image Computing and Computer-Assisted Interven- tion

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.942114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:0e050a0a28eb63a336775e0e6fdadf794b5cc9247c2291d27e7b692cbd56a54b

Observation d79dd6a8-fcc1-4aeb-9b57-405b1d1d5168 · outbound

This paper cites Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.937580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:3c1331e7fcd3d6c413cdf4fe70c22dbb0c4b4244a25c720ddc4151fc6c9aa7e1

Observation ebe5a08d-d339-4d32-8a94-4e2bc8cadaa0 · outbound

This paper cites Unveiling the potential of diffusion model-based framework with transformer for hyperspectral image classification.Sci- entific Reports, 14(1):8438.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Unveiling the potential of diffusion model-based framework with transformer for hyperspectral image classification.Sci- entific Reports, 14(1):8438

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.955073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:8c9b21d4d005f7caa18cc4237f06410e69b7d811560c1892fb76eb4f6dc0c058

Observation 1b07c002-6822-43f4-aec8-19c8d6257c62 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.Inter- national Conference on Machine Learning.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Deep unsupervised learning using nonequilibrium thermodynamics.Inter- national Conference on Machine Learning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.893682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:fb1fbd8ae3fa8006c36c41efaf3c523a984e2cfc1923c32b9e1561c9b078fa68

Observation 2566b711-7e73-4c0c-aa69-2a971c84615e · outbound

This paper cites Crs-diff: Controllable remote sensing image gener- ation with diffusion model.IEEE Transactions on Geoscience and Remote Sensing.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Crs-diff: Controllable remote sensing image gener- ation with diffusion model.IEEE Transactions on Geoscience and Remote Sensing

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.904824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:98ecef8aa867b85548b8504fb250cb83611394cd1da8d628b8c3a16ae21f379c

Observation 1228377c-ab4d-4824-b99c-1654d2480f1a · outbound

This paper cites Swimdiff: Scene-wide matching con- trastive learning with diffusion constraint for remote sensing image.IEEE Transactions on Geoscience and Remote Sensing.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Swimdiff: Scene-wide matching con- trastive learning with diffusion constraint for remote sensing image.IEEE Transactions on Geoscience and Remote Sensing

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.925296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:5946fa63b16fed958b70dee746606a6e09e0fc7dc11fb42f072004ffb90e9218

Observation 8b48ddc7-ef4f-41a9-bea7-6deb08563b09 · outbound

This paper cites Satsynth: Augmenting image- mask pairs through diffusion models for aerial seman- tic segmentation.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Satsynth: Augmenting image- mask pairs through diffusion models for aerial seman- tic segmentation

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.950608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:719fcda2a7c7a9bb226fd7d052bff487ba84aebaee93e9bdf87e69a8b7ff96c0

Observation d4816e8b-c20e-42b1-8820-ed72fd56ed32 · outbound

This paper cites Galileo: Learning global & local features of many remote sensing modalities.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Galileo: Learning global & local features of many remote sensing modalities

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.876757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:d2b065af2c7008f44e6335a280a2ca14be597234c2c57ead75f2e61a16a94373

Observation 03f95b7a-26a0-41a8-9f82-9b5187a52a27 · outbound

This paper cites Panop- ticon: Advancing any-sensor foundation models for earth observation.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Panop- ticon: Advancing any-sensor foundation models for earth observation

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.908669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:b36f83c90b01eb2b5d56683a5f6725288e5ccfef58bf1ae1d02b2f2cdec285a3

Observation 08d9acb2-1cc7-4822-9c16-8f2faeaa4bdc · outbound

This paper cites Semantic guided large scale factor remote sensing image super-resolution with generative diffusion prior.ISPRS Journal of Photogrammetry and Remote Sensing, 220:125–138.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Semantic guided large scale factor remote sensing image super-resolution with generative diffusion prior.ISPRS Journal of Photogrammetry and Remote Sensing, 220:125–138

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.889710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:5ab3c8b50e1edc54adf90ed9235b52abbc0792540e52861c84405cb253d9a87f

Observation 4c74c2b0-3d85-4dc7-9440-a1e615e6508c · outbound

This paper cites Sar-to-optical image translation using supervised cycle-consistent adversar- ial networks.Ieee Access, 7:129136–129149.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Sar-to-optical image translation using supervised cycle-consistent adversar- ial networks.Ieee Access, 7:129136–129149

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.901079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:76b3561c71b1bf554eb611f8345ade4a5a0b259594ff051d078660395d2bc5ee

Observation e0355168-e826-4664-8fff-9c9911f6e938 · outbound

This paper cites Idf-cr: Iterative dif- fusion process for divide-and-conquer cloud removal in remote-sensing images.IEEE Transactions on Geo- science and Remote Sensing.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Idf-cr: Iterative dif- fusion process for divide-and-conquer cloud removal in remote-sensing images.IEEE Transactions on Geo- science and Remote Sensing

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.885030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:928263fb31a5dea499d44f8c8029f4d0a306d103b7a0af237187b73b3730a3fa

Observation b05ad90e-8278-4e8b-9182-55eba57b92d8 · outbound

This paper cites Es- rgan: Enhanced super-resolution generative adversar- ial networks.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Es- rgan: Enhanced super-resolution generative adversar- ial networks

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.929119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:c4e7e9dc122e80aeee5ae9d964ec7c70a7f951c575b055f8f21d0c2809436705

Observation dc70a45d-9588-42ee-b64b-96dd1ca4f445 · outbound

This paper cites Stewart, Thomas Dujardin, Nikolaos Ioannis Bountos, Angelos Zavras, Franziska Gerken, Ioannis Papoutsis, Laura Leal-Taix ´e, and Xiao Xiang Zhu.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Stewart, Thomas Dujardin, Nikolaos Ioannis Bountos, Angelos Zavras, Franziska Gerken, Ioannis Papoutsis, Laura Leal-Taix ´e, and Xiao Xiang Zhu

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.920961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:4e2d66f1666b69473351847136e94f27aeaeef836a60690e1e23920b8a28cbab

Observation 9c398245-d341-4ff0-8b99-60a1983c16ad · outbound

This paper cites Gcd-ddpm: A generative change detec- tion model based on difference-feature guided ddpm.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Gcd-ddpm: A generative change detec- tion model based on difference-feature guided ddpm

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.946952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:251dabf3af1309dfef63975de0869ca8a807822e9cf62770c60fb745b7796acd

Observation 35d687f1-650f-4069-a892-be4bbc44ffc0 · outbound

This paper cites Xiong, Y.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Xiong, Y

Reference 63

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T16:40:10.453529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:f25dd4214df250195fdeab138af4ff973185b26147c29035dddf741190e52089

Observation b102be87-ff5c-4740-a405-adfda1f10608 · outbound

This paper cites Metaearth: A generative founda- tion model for global-scale remote sensing image gen- eration.IEEE Transactions on Pattern Analysis and Machine Intelligence, 47(3):1764–1781.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Metaearth: A generative founda- tion model for global-scale remote sensing image gen- eration.IEEE Transactions on Pattern Analysis and Machine Intelligence, 47(3):1764–1781

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-05-15T16:40:10.912684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T16:40:02.055902Z digest=sha256:e3dff8dce80ea1f62d670ff561867b2ea67c253ad749b6ca15a237b017e486c1

Observation 77ab54c3-fee0-46e6-95fe-e3a1edd0e477 · outbound

This paper cites DiffUCD:Unsupervised Hyperspectral Image Change Detection with Semantic Correlation Diffusion Model.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data DiffUCD:Unsupervised Hyperspectral Image Change Detection with Semantic Correlation Diffusion Model

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This paper cites Zhang, G.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Zhang, G

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This paper cites Changen2: Multi-temporal remote sensing generative change foundation model.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Changen2: Multi-temporal remote sensing generative change foundation model

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This paper cites Exploring multi- timestep multi-stage diffusion features for hyperspec- tral image classification.IEEE Transactions on Geo- science and Remote Sensing.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Exploring multi- timestep multi-stage diffusion features for hyperspec- tral image classification.IEEE Transactions on Geo- science and Remote Sensing

Reference 68

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This paper cites Condition.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Condition

Reference 69

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This paper cites Example real-image thumbnails are provided for comparison.

COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data Example real-image thumbnails are provided for comparison

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Pith citing papers

Observation 422e5da6-c189-4e19-a032-24c9bcfd6b5f · inbound

Now We Know? A Systematic Comparison of TerraMind and THOR cites this paper.

Now We Know? A Systematic Comparison of TerraMind and THOR COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Data

Reference 24

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