Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T17:51:54.183590Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T17:51:54.183590Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-08T13:40:25.697869Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T18:51:07.796875Z
67 of 67 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 0a46af35-47b0-4e2f-adfb-cbc9043cb37b · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
Reference 1
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Observation 23b81ef7-7cd5-4302-b374-87d5e4845b45 · outbound
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
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Unresolved cited work
Reference 3
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Observation 2b960543-0043-45ca-860a-762ab7a5a88e · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration D-Flow: Differentiating through Flows for Controlled Generation
Reference 4
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Observation afe25d64-f288-47bd-8744-a894b3296d09 · outbound
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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Observation 34eec0de-1f3f-411c-af0c-dd051a633506 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Pix2video: Video editing using image diffusion
Reference 6
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Observation cbcc0415-1fab-4d69-9fa0-b692c2246c5c · outbound
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
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Stargan v2: Diverse image synthesis for multiple domains
Reference 8
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Observation 830fa764-70f0-4f7c-b6e1-ff6e8f3d97b3 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Diffusion Posterior Sampling for General Noisy Inverse Problems
Reference 9
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Observation be14b42b-6623-4f97-9e3a-e70ee825d2c8 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Fluxs- pace: Disentangled semantic editing in rectified flow mod- els
Reference 10
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Observation 49653e43-0684-4b08-8599-247fcfcb3b49 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing
Reference 11
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Observation cefe2ba3-faeb-4250-bff2-05afee3cc70d · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Diffusion models beat gans on image synthesis
Reference 12
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Observation da6dd92c-8cee-4382-8f36-802c011b3613 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration guided-diffusion
Reference 13
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Observation 0890af7b-06cc-486e-a2ef-c0c203fa01e7 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Scaling recti- fied flow transformers for high-resolution image synthesis
Reference 14
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Observation e0ffe6c9-8ca9-403b-826f-686a050ba15b · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration TokenFlow: Consistent Diffusion Features for Consistent Video Editing
Reference 15
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Observation 64241eb5-1cdd-43ba-a6cc-8e7ecd53d3c8 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Gonzalez and Richard E
Reference 16
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Observation d6930838-ac92-471b-93fa-f4f448aa0a95 · outbound
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
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
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Style aligned image generation via shared atten- tion
Reference 19
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Observation 622d8be0-6eff-4e15-8e06-ad202fb08a68 · outbound
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
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Denoising dif- fusion probabilistic models
Reference 21
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Observation 4b8ef620-65f1-49b2-b758-379cd64758e3 · outbound
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
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
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
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
FlowSteer: Conditioning Flow Field for Consistent Image Restoration FlowAlign: Trajectory-Regularized, Inversion-Free Flow-based Image Editing
Reference 26
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Unavailable: canonical work link unavailable.
Observation 1b7d6960-3f89-4549-9ccd-8fd602b8b67f · outbound
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
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
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
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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Unavailable: canonical work link unavailable.
Observation f880805f-9970-4e61-8fea-90ecdcd7eb41 · outbound
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
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Flow Matching for Generative Modeling
Reference 32
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Observation 63aa18c2-4bf5-4488-af89-1915fd5fed06 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Video-p2p: Video editing with cross-attention control
Reference 33
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Unavailable: canonical work link unavailable.
Observation 7a6d2fed-5178-4257-aea1-d7b89f04c3b6 · outbound
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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Observation 865b65ac-36fb-4884-9d4c-9c01759ac8ea · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Deep learning face attributes in the wild
Reference 35
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Observation 5efbe621-e86e-4fbe-adb4-e43a42b6c8b9 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
Reference 36
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Observation 0908ddab-69fb-49f8-9f4f-b61188540d54 · outbound
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
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
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Improved denoising diffusion probabilistic models
Reference 39
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Observation 77924f1f-3c2e-42ee-9cca-6946f01121ad · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Understanding the latent space of diffusion models through the lens of riemannian geometry
Reference 40
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Observation 3f28887b-1331-4dba-ba45-4bb7c145511b · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Muckley, Ricky T
Reference 41
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Observation 6f5d7c20-628b-4cff-a060-5bd7411c384c · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Fatezero: Fus- ing attentions for zero-shot text-based video editing
Reference 42
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Observation 86a3f603-3223-4d2b-ba31-b420040d9fb2 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Learning transferable visual models from natural language supervi- sion
Reference 43
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Observation c0fc000d-f339-4874-a015-87c2a98112d1 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration High-resolution image synthesis with latent diffusion models
Reference 44
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Observation 451825e1-74c2-4ad9-a6a5-bc8b44129fd5 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Semantic im- age inversion and editing using rectified stochastic differen- tial equations
Reference 45
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Observation 497dbcc6-61ab-4a00-97b5-e9df54c0323d · outbound
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,
Reference 46
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Observation ac608de0-7d86-409f-a0d0-9593f0c2b203 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Progressive prompt de- tailing for improved alignment in text-to-image generative models
Reference 47
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Observation 6357fa3d-4f3c-4859-86b9-2e4119b77bb5 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Fast high- resolution image synthesis with latent adversarial diffusion distillation
Reference 48
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Observation 3ae5c445-9061-4aac-be2c-40d5435fba82 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Diff2flow: Training flow matching models via dif- fusion model alignment
Reference 49
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Observation b3fc4ed8-f7dc-4ede-bced-c022d0cbdb5a · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Parallel sampling of diffusion models.Ad- vances in Neural Information Processing Systems, 36:4263– 4276, 2023
Reference 50
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Observation 06a89faf-30a6-44b7-8dfb-88289cf41cd4 · outbound
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
Reference 51
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Observation 9d5ebdae-48b1-4e5e-963d-296e9287fe0d · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Denoising Diffusion Implicit Models
Reference 52
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Observation b3f56ed4-7ca6-4605-b967-f98b7e15f451 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Score-Based Generative Modeling through Stochastic Differential Equations
Reference 53
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Observation 834968c5-a252-45db-9c89-001acfe147bc · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Stable Diffusion 3.https://stability
Reference 54
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Observation 43e5383b-3bd6-455a-8105-d95c89afed77 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Plug-and-play diffusion features for text-driven image-to-image translation
Reference 56
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Observation c04feecf-f82e-4331-91ec-871a68f0e84e · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Plug-and-play priors for model based re- construction
Reference 57
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Observation 26eb756a-19bd-47ec-9810-668a7cd5735a · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Edict: Exact diffusion inversion via coupled transformations
Reference 58
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Observation 4a9ae2f9-6a7a-4b51-ad14-5fb31e291b51 · outbound
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
Reference 59
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Observation 20695e71-0039-488d-9282-cdf8c1f5c86a · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Taming Rectified Flow for Inversion and Editing
Reference 60
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Observation b36346fb-5f49-415e-aabf-3d19cbf3d164 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Point2pix- zero: Point-driven refined diffusion for multi-object image editing.Pattern Recognition, page 112041, 2025
Reference 61
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Observation 2835152b-ad15-43cd-abe7-4dc0cba5a68d · outbound
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
Reference 62
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Observation 45ffb712-288d-47b3-811b-c4f393b5f0e5 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Paint by example: Exemplar-based image editing with diffusion mod- els
Reference 63
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Observation 9fe47656-9684-4830-950c-fd86dd7535ca · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Text-to-Image Rectified Flow as Plug-and-Play Priors
Reference 64
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Observation 6ea66d36-3f22-4059-8994-6768d21b1a5e · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration The unreasonable effectiveness of deep features as a perceptual metric
Reference 65
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Observation ccac9e56-ecce-4692-8158-df4059236c2b · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Real- world image variation by aligning diffusion inversion chain
Reference 66
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Observation b00f908d-749f-4f36-99d8-75833435bf32 · outbound
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
Reference 67
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Observation d507cc5c-4c82-4504-bee3-59dcd6d086e2 · outbound
FlowSteer: Conditioning Flow Field for Consistent Image Restoration Denoising dif- fusion models for plug-and-play image restoration
Reference 68
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Observation ecc36725-fbd3-40b7-8181-aae2347e4e40 · inbound
Null-Space Flow Matching for MIMO Channel Estimation in Latency-Constrained Systems FlowSteer: Conditioning Flow Field for Consistent Image Restoration
Reference 16
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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.