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Paper Citation Record · LEDGER

FlowSteer: Conditioning Flow Field for Consistent Image Restoration

As of 6 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 1 inbound Pith citation observation for arXiv:2512.08125.

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

pith.paper-citation-record.v1
2512.08125 v2

Coverage vector

measured 67 of 67 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T17:51:54.183590Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T13:40:25.697869Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T18:51:07.796875Z

Reference resolution

67 of 67 outbound references displayed

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Outbound references

Observation 0a46af35-47b0-4e2f-adfb-cbc9043cb37b · outbound

This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 1

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source=pdf_text observed=2026-08-03T17:51:50.603012Z digest=sha256:c2a561c3dda2a537ebd396f4b5f8fcf3258839c8e61664808de5230d1a22694d

Observation 23b81ef7-7cd5-4302-b374-87d5e4845b45 · outbound

This paper cites Blended diffusion for text-driven editing of natural images.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Blended diffusion for text-driven editing of natural images

Reference 2

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Observation ffe590fa-57f7-41bc-897c-2be88249e3c5 · outbound

This paper cites an unresolved cited work.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Unresolved cited work

Reference 3

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Observation 2b960543-0043-45ca-860a-762ab7a5a88e · outbound

This paper cites D-Flow: Differentiating through Flows for Controlled Generation.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration D-Flow: Differentiating through Flows for Controlled Generation

Reference 4

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source=pdf_text observed=2026-08-03T17:51:50.963485Z digest=sha256:3eb28d52cd8874704702f35d26a4346e45cb567152fe1e9c34196177ab88d6c8

Observation afe25d64-f288-47bd-8744-a894b3296d09 · outbound

This paper cites Masactrl: Tuning-free mu- tual self-attention control for consistent image synthesis and editing.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Masactrl: Tuning-free mu- tual self-attention control for consistent image synthesis and editing

Reference 5

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source=pdf_text observed=2026-08-03T17:51:51.116774Z digest=sha256:c0da1f7881e292e819542d407030382ef48ecb74136ce618d42e7bd3a0a113ec

Observation 34eec0de-1f3f-411c-af0c-dd051a633506 · outbound

This paper cites Pix2video: Video editing using image diffusion.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Pix2video: Video editing using image diffusion

Reference 6

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source=pdf_text observed=2026-08-03T17:51:51.239842Z digest=sha256:916ca4ca93bb8bc9bb52aac52721a36a5837af67ba8c4b9fd71badc21160af88

Observation cbcc0415-1fab-4d69-9fa0-b692c2246c5c · outbound

This paper cites Ilvr: Conditioning method for denoising diffusion probabilistic models.2021 IEEE/CVF International Conference on Computer Vision (ICCV), pages 14347–14356, 2021.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Ilvr: Conditioning method for denoising diffusion probabilistic models.2021 IEEE/CVF International Conference on Computer Vision (ICCV), pages 14347–14356, 2021

Reference 7

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Observation b99bffbc-f8a3-4567-b53d-d0dfa90b787a · outbound

This paper cites Stargan v2: Diverse image synthesis for multiple domains.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Stargan v2: Diverse image synthesis for multiple domains

Reference 8

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source=pdf_text observed=2026-08-03T17:51:51.537919Z digest=sha256:e128ca521dbb6710ade8c2dd6542d7c7a0cb2fd46f7e25d9f7d71373d7696b2f

Observation 830fa764-70f0-4f7c-b6e1-ff6e8f3d97b3 · outbound

This paper cites Diffusion Posterior Sampling for General Noisy Inverse Problems.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Diffusion Posterior Sampling for General Noisy Inverse Problems

Reference 9

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source=pdf_text observed=2026-08-03T17:51:51.779297Z digest=sha256:8281bcf0c996930a59d509020824bd59d75a2c633bb527ceb5af8a5c302527bb

Observation be14b42b-6623-4f97-9e3a-e70ee825d2c8 · outbound

This paper cites Fluxs- pace: Disentangled semantic editing in rectified flow mod- els.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Fluxs- pace: Disentangled semantic editing in rectified flow mod- els

Reference 10

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source=pdf_text observed=2026-08-03T17:51:51.921922Z digest=sha256:b76d2b920101580e9aeb81bbb4f7097112e7ed1b6325d6a53c256a7d8b564dab

Observation 49653e43-0684-4b08-8599-247fcfcb3b49 · outbound

This paper cites FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing

Reference 11

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source=pdf_text observed=2026-08-03T17:51:52.086212Z digest=sha256:2aee050feacbee30d8a699da89e3a29bfda8860b4d5e49452e86c8a435af3266

Observation cefe2ba3-faeb-4250-bff2-05afee3cc70d · outbound

This paper cites Diffusion models beat gans on image synthesis.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Diffusion models beat gans on image synthesis

Reference 12

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source=pdf_text observed=2026-08-03T17:51:52.149477Z digest=sha256:58c27c6561633a7b65b7e1518219492e26452bd324b49fd1fadf8f7121297266

Observation da6dd92c-8cee-4382-8f36-802c011b3613 · outbound

This paper cites guided-diffusion.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration guided-diffusion

Reference 13

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source=pdf_text observed=2026-08-03T17:51:52.196417Z digest=sha256:3e36947adf610414c74e02fa20e127ac80d9f5f32bbf6353ae04529d427f7088

Observation 0890af7b-06cc-486e-a2ef-c0c203fa01e7 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 14

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source=pdf_text observed=2026-08-03T17:51:52.251490Z digest=sha256:4e01f6824c6504c09302cce8a034403da50554ba5b17534ce3a3b44c16140b7b

Observation e0ffe6c9-8ca9-403b-826f-686a050ba15b · outbound

This paper cites TokenFlow: Consistent Diffusion Features for Consistent Video Editing.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration TokenFlow: Consistent Diffusion Features for Consistent Video Editing

Reference 15

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source=pdf_text observed=2026-08-03T17:51:52.304554Z digest=sha256:f3881a1c28092f32d38faf46ff05c5ae32d315479a1fa40e5bdd25c2c8ac07bf

Observation 64241eb5-1cdd-43ba-a6cc-8e7ecd53d3c8 · outbound

This paper cites Gonzalez and Richard E.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Gonzalez and Richard E

Reference 16

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source=pdf_text observed=2026-08-03T17:51:52.358815Z digest=sha256:370153ef3eb716faf27c95ae1f134ae9dd2b7a73ee5ad6de03a3265124534f26

Observation d6930838-ac92-471b-93fa-f4f448aa0a95 · outbound

This paper cites Nagy, and Dianne P.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Nagy, and Dianne P

Reference 17

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Observation e1b78479-e64a-4682-b7a7-b8953cd14fd8 · outbound

This paper cites Prompt-to-prompt im- age editing with cross attention control.The Eleventh In- ternational Conference on Learning Representations (ICLR),.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Prompt-to-prompt im- age editing with cross attention control.The Eleventh In- ternational Conference on Learning Representations (ICLR),

Reference 18

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Observation e96f015e-1a7d-4d5d-9eeb-962d9c07901c · outbound

This paper cites Style aligned image generation via shared atten- tion.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Style aligned image generation via shared atten- tion

Reference 19

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source=pdf_text observed=2026-08-03T17:51:52.518862Z digest=sha256:a5a29d618c6bd4e78d7d95f1cc8682d9917cb316d53838e1bce6c2e3647460e6

Observation 622d8be0-6eff-4e15-8e06-ad202fb08a68 · outbound

This paper cites Classifier-free diffusion guidance, 2021.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Classifier-free diffusion guidance, 2021

Reference 20

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Observation e04803f0-e90a-4f1e-9da1-a61f6611f9cf · outbound

This paper cites Denoising dif- fusion probabilistic models.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Denoising dif- fusion probabilistic models

Reference 21

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source=pdf_text observed=2026-08-03T17:51:52.626089Z digest=sha256:dc956a1d32ff308f4d15cef4e56be6095be758ce4e4689be335989b91110a93c

Observation 4b8ef620-65f1-49b2-b758-379cd64758e3 · outbound

This paper cites UniEdit-Flow: Unleashing Inversion and Editing in the Era of Flow Models.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration UniEdit-Flow: Unleashing Inversion and Editing in the Era of Flow Models

Reference 22

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Observation b8a6764f-9193-4e88-9afe-68c2cb9f8061 · outbound

This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 23

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Observation c64523a8-0ff7-4419-a934-e53369bd27da · outbound

This paper cites Snips: Solving noisy inverse problems stochastically.Advances in Neural Information Processing Systems, 34:21757–21769,.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Snips: Solving noisy inverse problems stochastically.Advances in Neural Information Processing Systems, 34:21757–21769,

Reference 24

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Observation c84f12ce-603c-4975-8911-c91d146c6a84 · outbound

This paper cites Denoising diffusion restoration models.Advances in Neural Information Processing Systems, 35:23593–23606,.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Denoising diffusion restoration models.Advances in Neural Information Processing Systems, 35:23593–23606,

Reference 25

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Observation e099fe64-e5e4-4419-aeae-96d21286998f · outbound

This paper cites FlowAlign: Trajectory-Regularized, Inversion-Free Flow-based Image Editing.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration FlowAlign: Trajectory-Regularized, Inversion-Free Flow-based Image Editing

Reference 26

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source=pdf_text observed=2026-08-03T17:51:52.978201Z digest=sha256:6880a650d2c9fb8d349f65c1d6214437e8ff7bb67e24244dc02952913302239a

Observation 1b7d6960-3f89-4549-9ccd-8fd602b8b67f · outbound

This paper cites Reflex: Text-guided editing of real images in rectified flow via mid-step feature extraction and attention 11 adaptation.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Reflex: Text-guided editing of real images in rectified flow via mid-step feature extraction and attention 11 adaptation

Reference 27

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Observation 21a095b1-61b2-44c3-a012-4fd319c9ceb7 · outbound

This paper cites Kingma and Max Welling.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Kingma and Max Welling

Reference 28

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Observation 18dde52c-f4c9-4052-9386-1a9af98112b2 · outbound

This paper cites Dual prompting image restoration with diffusion transformers.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Dual prompting image restoration with diffusion transformers

Reference 29

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Observation 0220f046-1534-46f3-a67a-94ec53d24768 · outbound

This paper cites Flowedit: Inversion- free text-based editing using pre-trained flow models.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Flowedit: Inversion- free text-based editing using pre-trained flow models

Reference 30

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source=pdf_text observed=2026-08-03T17:51:53.258966Z digest=sha256:b05531e8f3760acbd8561f53e253572035422c49cc40675750dcae92e9b5932e

Observation f880805f-9970-4e61-8fea-90ecdcd7eb41 · outbound

This paper cites FLUX.https://github.com/ black-forest-labs/flux, 2024.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration FLUX.https://github.com/ black-forest-labs/flux, 2024

Reference 31

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Observation 656fba88-f205-4554-b924-b4142821c16f · outbound

This paper cites Flow Matching for Generative Modeling.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Flow Matching for Generative Modeling

Reference 32

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source=pdf_text observed=2026-08-03T17:51:53.440806Z digest=sha256:e09fcb406018f2af61f3a2febcc1e6eeb5ff08d41a28beb555d6b63cfe174467

Observation 63aa18c2-4bf5-4488-af89-1915fd5fed06 · outbound

This paper cites Video-p2p: Video editing with cross-attention control.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Video-p2p: Video editing with cross-attention control

Reference 33

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source=pdf_text observed=2026-08-03T17:51:53.552263Z digest=sha256:b8df0b17a8dd63970b89b1ecbeb7083dcd7b78fd52d2565fe795feeaf147c314

Observation 7a6d2fed-5178-4257-aea1-d7b89f04c3b6 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 34

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source=pdf_text observed=2026-08-03T17:51:53.592645Z digest=sha256:26578d531d9c81c33cef26cc70b709ef7a9f85798973f0001d0de197d5e661ec

Observation 865b65ac-36fb-4884-9d4c-9c01759ac8ea · outbound

This paper cites Deep learning face attributes in the wild.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Deep learning face attributes in the wild

Reference 35

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source=pdf_text observed=2026-08-03T17:51:53.712247Z digest=sha256:26d41e16dd0ab01248710daa69e02a7de6a65e655ff92df464f8357252e0dc74

Observation 5efbe621-e86e-4fbe-adb4-e43a42b6c8b9 · outbound

This paper cites PnP-Flow: Plug-and-Play Image Restoration with Flow Matching.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration PnP-Flow: Plug-and-Play Image Restoration with Flow Matching

Reference 36

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source=pdf_text observed=2026-08-03T17:51:53.816120Z digest=sha256:20ec8f45f5857014f377742b5f7cb428f9334b2cbecfd56377c5333542646789

Observation 0908ddab-69fb-49f8-9f4f-b61188540d54 · outbound

This paper cites SDEdit: Guided image synthesis and editing with stochastic differential equa- tions.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration SDEdit: Guided image synthesis and editing with stochastic differential equa- tions

Reference 37

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Observation e0370a48-3b87-4cb0-af9a-0dc49850db41 · outbound

This paper cites T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models

Reference 38

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Observation b31bddbe-adc3-43f2-8baa-e3b611044f14 · outbound

This paper cites Improved denoising diffusion probabilistic models.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Improved denoising diffusion probabilistic models

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source=pdf_text observed=2026-08-03T17:51:54.009319Z digest=sha256:0969f149b3921bc4e58b1a3e1bf2d39224c72904c97cca79b9084bdfe5667ede

Observation 77924f1f-3c2e-42ee-9cca-6946f01121ad · outbound

This paper cites Understanding the latent space of diffusion models through the lens of riemannian geometry.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Understanding the latent space of diffusion models through the lens of riemannian geometry

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source=pdf_text observed=2026-08-03T17:51:54.037193Z digest=sha256:052022e33443bd30f7f98d895b793897cc1c66921b49befb6a5c27a45f508963

Observation 3f28887b-1331-4dba-ba45-4bb7c145511b · outbound

This paper cites Muckley, Ricky T.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Muckley, Ricky T

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source=pdf_text observed=2026-08-03T17:51:54.083935Z digest=sha256:5026a7e8bb745c75cec3498342f44a60077b87fa1302cf188855cbd35c457830

Observation 6f5d7c20-628b-4cff-a060-5bd7411c384c · outbound

This paper cites Fatezero: Fus- ing attentions for zero-shot text-based video editing.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Fatezero: Fus- ing attentions for zero-shot text-based video editing

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source=pdf_text observed=2026-08-03T17:51:54.092472Z digest=sha256:848138aca787a016f6ee316c240d87260a0ce3ab2a3f7696722a4ea9abe161b4

Observation 86a3f603-3223-4d2b-ba31-b420040d9fb2 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Learning transferable visual models from natural language supervi- sion

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source=pdf_text observed=2026-08-03T17:51:54.116353Z digest=sha256:c1727f743c3558cb9988a65ad3c5038ee43e444bf832f72e37d86207215dfee7

Observation c0fc000d-f339-4874-a015-87c2a98112d1 · outbound

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

FlowSteer: Conditioning Flow Field for Consistent Image Restoration High-resolution image synthesis with latent diffusion models

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source=pdf_text observed=2026-08-03T17:51:54.122528Z digest=sha256:fc612c47fb614a4b8d9af2778e15a1cad5325c25c375ac8c22ffcc1224096e6c

Observation 451825e1-74c2-4ad9-a6a5-bc8b44129fd5 · outbound

This paper cites Semantic im- age inversion and editing using rectified stochastic differen- tial equations.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Semantic im- age inversion and editing using rectified stochastic differen- tial equations

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source=pdf_text observed=2026-08-03T17:51:54.125296Z digest=sha256:4583ea1e94a055d0eac0025cef7a3b60bbf7a19d57091e883d64af83f820a252

Observation 497dbcc6-61ab-4a00-97b5-e9df54c0323d · outbound

This paper cites Image super- resolution via iterative refinement.IEEE transactions on pattern analysis and machine intelligence, 45(4):4713–4726,.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Image super- resolution via iterative refinement.IEEE transactions on pattern analysis and machine intelligence, 45(4):4713–4726,

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source=pdf_text observed=2026-08-03T17:51:54.127812Z digest=sha256:424646e99d2182ac26d3a73f6793ffde2cfc79f4dba5c5188db85ea7ad695b68

Observation ac608de0-7d86-409f-a0d0-9593f0c2b203 · outbound

This paper cites Progressive prompt de- tailing for improved alignment in text-to-image generative models.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Progressive prompt de- tailing for improved alignment in text-to-image generative models

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source=pdf_text observed=2026-08-03T17:51:54.130676Z digest=sha256:41697da7a53e1bb4bfd1a9a534603a97bf0f1e045f35e17be2daefd2c51908b1

Observation 6357fa3d-4f3c-4859-86b9-2e4119b77bb5 · outbound

This paper cites Fast high- resolution image synthesis with latent adversarial diffusion distillation.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Fast high- resolution image synthesis with latent adversarial diffusion distillation

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source=pdf_text observed=2026-08-03T17:51:54.133090Z digest=sha256:b5b602ceb47db2089d80f6c2f51d19bdacb000d1ee5b9273aa0993b57310b48d

Observation 3ae5c445-9061-4aac-be2c-40d5435fba82 · outbound

This paper cites Diff2flow: Training flow matching models via dif- fusion model alignment.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Diff2flow: Training flow matching models via dif- fusion model alignment

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source=pdf_text observed=2026-08-03T17:51:54.135555Z digest=sha256:592c45e8fb480dd2e01e546fca93cc34371a2118ab9cad8ab34dbe7967ca61a3

Observation b3fc4ed8-f7dc-4ede-bced-c022d0cbdb5a · outbound

This paper cites Parallel sampling of diffusion models.Ad- vances in Neural Information Processing Systems, 36:4263– 4276, 2023.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Parallel sampling of diffusion models.Ad- vances in Neural Information Processing Systems, 36:4263– 4276, 2023

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source=pdf_text observed=2026-08-03T17:51:54.137967Z digest=sha256:a04b1b411d339fd99938f7fe1827c76d8c9c680126970f473ad5bb01ed42dad1

Observation 06a89faf-30a6-44b7-8dfb-88289cf41cd4 · outbound

This paper cites Solving inverse problems with latent diffusion models via hard data consistency.The Eleventh International Conference on Learning Representa- tions (ICLR), 2024.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Solving inverse problems with latent diffusion models via hard data consistency.The Eleventh International Conference on Learning Representa- tions (ICLR), 2024

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source=pdf_text observed=2026-08-03T17:51:54.140540Z digest=sha256:4c37d2396ada4094ea08f0a869db0dcb848969e1302c87e4bf32667459572756

Observation 9d5ebdae-48b1-4e5e-963d-296e9287fe0d · outbound

This paper cites Denoising Diffusion Implicit Models.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Denoising Diffusion Implicit Models

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source=pdf_text observed=2026-08-03T17:51:54.143289Z digest=sha256:d2ef2a6c0e03b3c33ac8d791eb4ff001ffa405e08ba5d9c49c28bf234b85504f

Observation b3f56ed4-7ca6-4605-b967-f98b7e15f451 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Score-Based Generative Modeling through Stochastic Differential Equations

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source=pdf_text observed=2026-08-03T17:51:54.146092Z digest=sha256:2a854fb21e41f9dc9d36a89d56cca4e05fe485ae3b1b1f5c3020f3b16eda99b5

Observation 834968c5-a252-45db-9c89-001acfe147bc · outbound

This paper cites Stable Diffusion 3.https://stability.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Stable Diffusion 3.https://stability

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source=pdf_text observed=2026-08-03T17:51:54.148766Z digest=sha256:dc20d50960c43d91e753691281f888d357c036631d709188ba9790b893bc2b22

Observation 43e5383b-3bd6-455a-8105-d95c89afed77 · outbound

This paper cites Plug-and-play diffusion features for text-driven image-to-image translation.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Plug-and-play diffusion features for text-driven image-to-image translation

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source=pdf_text observed=2026-08-03T17:51:54.153917Z digest=sha256:b60f99fee9c9343c3c7ef05a6fc691c512cd13efa623cbc3accface0187bff19

Observation c04feecf-f82e-4331-91ec-871a68f0e84e · outbound

This paper cites Plug-and-play priors for model based re- construction.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Plug-and-play priors for model based re- construction

Reference 57

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source=pdf_text observed=2026-08-03T17:51:54.156428Z digest=sha256:7c8cbe6412d2742885da4bedebc5f299630be35ad4da6f02bbecccd631940964

Observation 26eb756a-19bd-47ec-9810-668a7cd5735a · outbound

This paper cites Edict: Exact diffusion inversion via coupled transformations.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Edict: Exact diffusion inversion via coupled transformations

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source=pdf_text observed=2026-08-03T17:51:54.158761Z digest=sha256:7120233abeb978d4b36e926ee2aaf6caf8e84e86caeb4f2613b8c790b0a0bb50

Observation 4a9ae2f9-6a7a-4b51-ad14-5fb31e291b51 · outbound

This paper cites Reconciling stochas- tic and deterministic strategies for zero-shot image restora- tion using diffusion model in dual.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Reconciling stochas- tic and deterministic strategies for zero-shot image restora- tion using diffusion model in dual

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source=pdf_text observed=2026-08-03T17:51:54.161052Z digest=sha256:74cb697969b64a2a23120d2abaf84d5b5e1afafee01090d0441d63e037dba760

Observation 20695e71-0039-488d-9282-cdf8c1f5c86a · outbound

This paper cites Taming Rectified Flow for Inversion and Editing.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Taming Rectified Flow for Inversion and Editing

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source=pdf_text observed=2026-08-03T17:51:54.163837Z digest=sha256:bda7528e83622cefe3bf3bcac0d2d1c2131b6a793597c13f501e2f484710d4ea

Observation b36346fb-5f49-415e-aabf-3d19cbf3d164 · outbound

This paper cites Point2pix- zero: Point-driven refined diffusion for multi-object image editing.Pattern Recognition, page 112041, 2025.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Point2pix- zero: Point-driven refined diffusion for multi-object image editing.Pattern Recognition, page 112041, 2025

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source=pdf_text observed=2026-08-03T17:51:54.166509Z digest=sha256:1d483cd5c15ef1aaa31d5c5805b26b740f3183e137365ca2d651e101cd19609e

Observation 2835152b-ad15-43cd-abe7-4dc0cba5a68d · outbound

This paper cites Zero-shot image restoration using denoising diffusion null-space model.The Eleventh International Conference on Learning Representa- tions (ICLR), 2023.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Zero-shot image restoration using denoising diffusion null-space model.The Eleventh International Conference on Learning Representa- tions (ICLR), 2023

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source=pdf_text observed=2026-08-03T17:51:54.168786Z digest=sha256:9187b7b12ec68a3e44770b075d5fcfe17f1d9270f0780dc3016fae1d8e747524

Observation 45ffb712-288d-47b3-811b-c4f393b5f0e5 · outbound

This paper cites Paint by example: Exemplar-based image editing with diffusion mod- els.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Paint by example: Exemplar-based image editing with diffusion mod- els

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source=pdf_text observed=2026-08-03T17:51:54.171125Z digest=sha256:9f6c04eb6b7da08935714caa00bf280505ac5755a9b150f9cd8f36a06a2ee53a

Observation 9fe47656-9684-4830-950c-fd86dd7535ca · outbound

This paper cites Text-to-Image Rectified Flow as Plug-and-Play Priors.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Text-to-Image Rectified Flow as Plug-and-Play Priors

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source=pdf_text observed=2026-08-03T17:51:54.173437Z digest=sha256:02aea46b04c38bbc407ba4f415bf79f4174a0af4c7d2c8d72fe807c8a021abe0

Observation 6ea66d36-3f22-4059-8994-6768d21b1a5e · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration The unreasonable effectiveness of deep features as a perceptual metric

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source=pdf_text observed=2026-08-03T17:51:54.176021Z digest=sha256:ec549a1ef6b790b6df4d42556110992dcb117e6fb46a36ea7ef4cb01f4345ec1

Observation ccac9e56-ecce-4692-8158-df4059236c2b · outbound

This paper cites Real- world image variation by aligning diffusion inversion chain.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Real- world image variation by aligning diffusion inversion chain

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source=pdf_text observed=2026-08-03T17:51:54.178597Z digest=sha256:4a9746dcd826cd661592d8d70329a84d736e9958d606e65496cdbb56aad2bb3f

Observation b00f908d-749f-4f36-99d8-75833435bf32 · outbound

This paper cites Flow priors for lin- ear inverse problems via iterative corrupted trajectory match- ing.Advances in Neural Information Processing Systems, 37:57389–57417, 2024.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Flow priors for lin- ear inverse problems via iterative corrupted trajectory match- ing.Advances in Neural Information Processing Systems, 37:57389–57417, 2024

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source=pdf_text observed=2026-08-03T17:51:54.180918Z digest=sha256:bbbe6fae7e7ed66eee1d942951334869dcb8347b8d174ab39aa77e86ef31dc50

Observation d507cc5c-4c82-4504-bee3-59dcd6d086e2 · outbound

This paper cites Denoising dif- fusion models for plug-and-play image restoration.

FlowSteer: Conditioning Flow Field for Consistent Image Restoration Denoising dif- fusion models for plug-and-play image restoration

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source=pdf_text observed=2026-08-03T17:51:54.183590Z digest=sha256:f64975801682d6306c81555b883ab6e3eed292353b52a7e0ba88ce0a843bd0a3

Pith citing papers

Observation ecc36725-fbd3-40b7-8181-aae2347e4e40 · inbound

Null-Space Flow Matching for MIMO Channel Estimation in Latency-Constrained Systems cites this paper.

Null-Space Flow Matching for MIMO Channel Estimation in Latency-Constrained Systems FlowSteer: Conditioning Flow Field for Consistent Image Restoration

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verified exact
arxiv_id, observed 2026-05-26T03:04:08.376947Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-08T13:40:25.697869Z digest=sha256:194de02265f0517f9d649c36172a7bae8c1e449be378697bc57c3dbf61e5e3eb