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Paper Citation Record · LEDGER

MACS: Measurement-Aware Consistency Sampling for Inverse Problems

As of 12 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2510.02208.

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

pith.paper-citation-record.v1
2510.02208 v3

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T12:45:35.621990Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

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Reference resolution

62 of 62 outbound references displayed

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Outbound references

Observation 4d041cb6-8884-44b7-8e67-f4d499b36b7b · outbound

This paper cites Solving inverse problems in medical imaging with score-based generative models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Solving inverse problems in medical imaging with score-based generative models,

Reference 1

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Observation cf419e5e-1ed6-4b31-8790-3ae6d7aec7b2 · outbound

This paper cites Compressed sensing us- ing generative models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Compressed sensing us- ing generative models,

Reference 2

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Observation 00d364ca-5328-4382-9030-2e6db7a58ad8 · outbound

This paper cites An overview of full-waveform inversion in exploration geophysics,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems An overview of full-waveform inversion in exploration geophysics,

Reference 3

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Observation 58daeb8f-7059-45bd-8bae-99ba047a86ef · outbound

This paper cites Video diffusion models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Video diffusion models,

Reference 4

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Observation 70125acc-13f2-4370-906d-4888c8e25427 · outbound

This paper cites Diffir2vr-zero: Zero-shot video restoration with diffusion- based image restoration models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Diffir2vr-zero: Zero-shot video restoration with diffusion- based image restoration models,

Reference 5

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Observation 4b68755e-055d-410f-b07c-4724b9ebffc7 · outbound

This paper cites Warped diffusion: Solving video inverse problems with image diffusion models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Warped diffusion: Solving video inverse problems with image diffusion models,

Reference 6

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Observation 80ee487e-a207-43d7-b9ae-1362392c0a10 · outbound

This paper cites Vision-XL: High definition video inverse problem solver using latent image diffusion models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Vision-XL: High definition video inverse problem solver using latent image diffusion models,

Reference 7

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Observation e4513e1a-5957-4e47-bc94-7dee6ebb48ea · outbound

This paper cites Solving video inverse problems using image diffusion models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Solving video inverse problems using image diffusion models,

Reference 8

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Observation c51b9d18-ccb3-45aa-bf57-5d4b3ee71816 · outbound

This paper cites Solving audio inverse prob- lems with a diffusion model,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Solving audio inverse prob- lems with a diffusion model,

Reference 9

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Observation 4da73747-dd53-4c6e-a422-856d67874031 · outbound

This paper cites Image denoising by sparse 3-D transform-domain collaborative filtering,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Image denoising by sparse 3-D transform-domain collaborative filtering,

Reference 10

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Observation 0b207c89-af45-4469-af3c-3cce1f4afdfb · outbound

This paper cites Image denoising via sparse and redundant representations over learned dictionaries,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Image denoising via sparse and redundant representations over learned dictionaries,

Reference 11

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Observation 700ba56d-2d2b-4a1c-a210-cb0d1c714803 · outbound

This paper cites Weighted nuclear norm minimization with application to image denoising,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Weighted nuclear norm minimization with application to image denoising,

Reference 12

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Observation df348bac-dd1d-4be3-a826-fe4b97c67725 · outbound

This paper cites Image denoising: The deep learning revolution and beyond—a survey paper,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Image denoising: The deep learning revolution and beyond—a survey paper,

Reference 13

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Observation 83af8e08-88fe-43da-b6ac-35c853d9130a · outbound

This paper cites A residual dense U-Net neural network for image denoising,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems A residual dense U-Net neural network for image denoising,

Reference 14

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Observation 1aed3f5b-ee8c-445f-9193-85ddeee0c6e3 · outbound

This paper cites Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration,

Reference 15

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Observation 582280c2-535a-471d-9d82-5b9dde12d400 · outbound

This paper cites High perceptual quality image denoising with a posterior sampling cGAN,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems High perceptual quality image denoising with a posterior sampling cGAN,

Reference 16

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Observation d9bd0a07-e0c9-4525-b9a8-176e16c71c44 · outbound

This paper cites Denoising diffusion probabilistic models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Denoising diffusion probabilistic models,

Reference 17

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Observation 90632289-bb29-4291-963c-44f3d61822a4 · outbound

This paper cites Generative modeling by estimating gradients of the data distribution,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Generative modeling by estimating gradients of the data distribution,

Reference 18

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Observation a8d7c224-aaa7-4afa-85fc-2fbc68f56bd6 · outbound

This paper cites Diffusion models beat GANs on image synthesis,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Diffusion models beat GANs on image synthesis,

Reference 19

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Observation 8096a61e-9a4e-41ad-9583-2e97bd4a013f · outbound

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

MACS: Measurement-Aware Consistency Sampling for Inverse Problems High- resolution image synthesis with latent diffusion models,

Reference 20

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Observation 32ec346c-f3c9-437f-8a55-b92099630035 · outbound

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

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Score-Based Generative Modeling through Stochastic Differential Equations

Reference 21

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Observation 5352242f-d0b0-4843-be24-d32526f828e8 · outbound

This paper cites Denoising diffusion restoration models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Denoising diffusion restoration models,

Reference 22

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Observation 2573e1d2-8d6f-4f79-8c2e-d994ee874fd0 · outbound

This paper cites Deep back-projection networks for super-resolution,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Deep back-projection networks for super-resolution,

Reference 23

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Observation 251aa141-579d-4b4e-b444-56b262f67203 · outbound

This paper cites Image super-resolution via iterative refinement,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Image super-resolution via iterative refinement,

Reference 24

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Observation 7f19704b-90c8-4bd0-b6b6-07d4115759ee · outbound

This paper cites Semantic image inpainting with deep generative models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Semantic image inpainting with deep generative models,

Reference 25

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Observation 380be501-cd85-4e1e-b144-fa8791fd0208 · outbound

This paper cites RePaint: Inpainting using denoising diffusion probabilistic mod- els,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems RePaint: Inpainting using denoising diffusion probabilistic mod- els,

Reference 26

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Observation 890c1c34-b8c1-4173-bbed-41e45222f420 · outbound

This paper cites DeblurGAN-v2: De- blurring (orders-of-magnitude) faster and better,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems DeblurGAN-v2: De- blurring (orders-of-magnitude) faster and better,

Reference 27

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Observation 96ece306-0d2f-479e-b2f2-28e5ad252513 · outbound

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

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Palette: Image-to-image diffusion models,

Reference 28

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Observation a137b472-14c9-49fe-a42e-1adb76b79682 · outbound

This paper cites Solving inverse problems with latent diffusion models via hard data consistency,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Solving inverse problems with latent diffusion models via hard data consistency,

Reference 29

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Observation d826c344-1186-4367-a48a-ff916ac9a92c · outbound

This paper cites SILO: Solving inverse problems with latent operators,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems SILO: Solving inverse problems with latent operators,

Reference 30

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Observation 0b0bff03-c082-4178-aae4-6567fdb3b85a · outbound

This paper cites Improving diffusion models for inverse problems using manifold constraints,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Improving diffusion models for inverse problems using manifold constraints,

Reference 31

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Observation 700d3292-29cb-44d2-81fd-27c1bddf304e · outbound

This paper cites Diffusion posterior sampling for general noisy inverse problems,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Diffusion posterior sampling for general noisy inverse problems,

Reference 32

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Observation b74440b3-8c55-4266-927b-858d5893d7e2 · outbound

This paper cites Decomposed diffusion sampler for accelerating large-scale inverse problems,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Decomposed diffusion sampler for accelerating large-scale inverse problems,

Reference 33

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Observation 967eac2e-801e-4c2c-8a96-8526c9fa9938 · outbound

This paper cites Solving 3D inverse problems using pre-trained 2D diffusion models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Solving 3D inverse problems using pre-trained 2D diffusion models,

Reference 34

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Observation 36165551-15dc-4de4-a4b2-9a56537db377 · outbound

This paper cites SNIPS: Solving noisy inverse problems stochastically,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems SNIPS: Solving noisy inverse problems stochastically,

Reference 35

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Observation c0d9812d-4492-4d2b-9f16-70ebcf268125 · outbound

This paper cites Pseudoinverse-guided diffusion models for inverse problems,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Pseudoinverse-guided diffusion models for inverse problems,

Reference 36

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Observation 8f77b5dc-1d8e-415f-93c4-bd6922f41895 · outbound

This paper cites Zero-shot image restoration using de- noising diffusion null-space model,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Zero-shot image restoration using de- noising diffusion null-space model,

Reference 37

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Observation e0d56845-35b0-40ee-b51c-36379bc495fb · outbound

This paper cites ILVR: Condition- ing method for denoising diffusion probabilistic models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems ILVR: Condition- ing method for denoising diffusion probabilistic models,

Reference 38

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Observation 99ab9ed2-57a3-45db-81cc-c2b054b42287 · outbound

This paper cites Direct diffusion bridge using data consistency for inverse problems,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Direct diffusion bridge using data consistency for inverse problems,

Reference 39

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source=pdf_text observed=2026-08-04T12:45:32.625436Z digest=sha256:a61dcb93e885733ef8f21fc83eb6cb0ad9e7b283b098c84324639fbd953f6a1e

Observation 576c4af1-1cfc-456d-aec6-e4cbd7512cef · outbound

This paper cites Denoising diffusion implicit models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Denoising diffusion implicit models,

Reference 40

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source=pdf_text observed=2026-08-04T12:45:32.753362Z digest=sha256:84259cf47d158a37712cfc094d5227a73c338adba6e442df450362e7af4a374e

Observation ac07c505-851c-4fb3-9ec0-bff93e5fa95d · outbound

This paper cites Consistency models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Consistency models,

Reference 41

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source=pdf_text observed=2026-08-04T12:45:32.863711Z digest=sha256:e344bb66a48fedbae622f87ca4e15239716b0788a4d4b8001691eed8ad6a4966

Observation 277e6b13-bde6-4c47-abd4-4d5ff8d918a3 · outbound

This paper cites Multistep Consistency Models.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Multistep Consistency Models

Reference 42

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source=pdf_text observed=2026-08-04T12:45:32.918748Z digest=sha256:357481d38683f638722aebc7ee79c9b0594973d6e1e829b1769b57f0fa416766

Observation badf8d1f-d322-49c5-9a25-37389a9efc59 · outbound

This paper cites Consistency Models Made Easy.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Consistency Models Made Easy

Reference 43

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source=pdf_text observed=2026-08-04T12:45:32.996772Z digest=sha256:a2d48eb33e7739b79c2d67f21ba30ba33f270e99cf4d51159151180fe4ef9090

Observation 997cb4d9-0a7b-4636-a87f-50c11c39ff7e · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 44

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source=pdf_text observed=2026-08-04T12:45:33.063084Z digest=sha256:97951fba93f66f32ee65dd14686968cd9ef3870c3b06fc0ab71c30bed61fdc37

Observation a78783a9-d69a-4f9e-b07e-dbc5ee3eecd7 · outbound

This paper cites LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 45

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source=pdf_text observed=2026-08-04T12:45:33.132743Z digest=sha256:867f01f4b3c95894d2b2100de9ae7c1b885eb10dadc021ca963e5ea4db23241e

Observation 6ee58323-581c-45af-9ec3-b8e7fae30cbc · outbound

This paper cites GANs trained by a two time-scale update rule converge to a local Nash equilibrium,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems GANs trained by a two time-scale update rule converge to a local Nash equilibrium,

Reference 46

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source=pdf_text observed=2026-08-04T12:45:33.190357Z digest=sha256:f55d0827a34127f5e1c8feb834f00116d2207900c378e820dfb6d1ece2760417

Observation cdc4b85a-0f07-43cf-a7b4-e6cd4539567c · outbound

This paper cites Demysti- fying MMD GANs,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Demysti- fying MMD GANs,

Reference 47

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source=pdf_text observed=2026-08-04T12:45:33.247650Z digest=sha256:fb32453ce1087cb1b1b276a8b43aa6a0644785b74d203450199734cfc08ab05f

Observation de7ad89f-2b70-4307-874f-a4e9085fb7b8 · outbound

This paper cites Image quality assessment: From error visibility to structural similarity,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Image quality assessment: From error visibility to structural similarity,

Reference 48

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source=pdf_text observed=2026-08-04T12:45:33.370699Z digest=sha256:3425bbb6f84756c8fb2deb34cd773d7c8d32d8589a3bb787f22b327c7af99f4d

Observation 491de452-d948-4855-a9f8-42d280e82462 · outbound

This paper cites Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

Reference 49

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source=pdf_text observed=2026-08-04T12:45:33.491406Z digest=sha256:d841706185801ab822cfa76607f8fb6e78d5b29a9ddb6f51431841402fdf7dfd

Observation 70178b41-0932-4fc8-973b-cf4be4ceba3d · outbound

This paper cites InvFusion: Bridging supervised and zero-shot diffusion for inverse problems,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems InvFusion: Bridging supervised and zero-shot diffusion for inverse problems,

Reference 50

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source=pdf_text observed=2026-08-04T12:45:33.673148Z digest=sha256:3c93073dc9c30d58b556c3831d5fe9ef2582b53c4b7eaa3a9e98805990062b18

Observation 382a8acb-1878-463f-b9f7-1783228ae6ae · outbound

This paper cites Loss-guided diffusion models for plug-and-play con- trollable generation,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Loss-guided diffusion models for plug-and-play con- trollable generation,

Reference 51

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source=pdf_text observed=2026-08-04T12:45:33.787310Z digest=sha256:06ea1dd1bb08d90efa703b56895917c9f75d0122b70c68f8620394ad95871999

Observation 587a762b-3e65-4c9c-ba5f-436effcdc338 · outbound

This paper cites DEFT: Efficient fine-tuning of diffusion models by learning the generalized h-transform,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems DEFT: Efficient fine-tuning of diffusion models by learning the generalized h-transform,

Reference 52

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source=pdf_text observed=2026-08-04T12:45:33.977543Z digest=sha256:0c06df4f06dbf772ea47d8ffd01c4583de4e91e5ad4e58c2d0182620e0416b12

Observation 4fe0d0a2-6ea0-4320-9045-63c0896039be · outbound

This paper cites A Survey on Diffusion Models for Inverse Problems.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems A Survey on Diffusion Models for Inverse Problems

Reference 53

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source=pdf_text observed=2026-08-04T12:45:34.100304Z digest=sha256:db0f2be9af23e170f80d267b73f4d8fac5b3b237b3d933c230c3c91ce3043329

Observation 241b84e3-7e4d-439f-9091-34cf4837da09 · outbound

This paper cites CoSIGN: Few-step guidance of consistency model to solve general inverse problems,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems CoSIGN: Few-step guidance of consistency model to solve general inverse problems,

Reference 54

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source=pdf_text observed=2026-08-04T12:45:34.229581Z digest=sha256:e36f57bf538f74121ecbd211b8458d2d047a8227c64df6d47fb321d47d9e7ed7

Observation b21215a3-ea4e-4c6c-8c0c-722d9f4e24ea · outbound

This paper cites Con- sistency models for scalable and fast simulation-based inference,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Con- sistency models for scalable and fast simulation-based inference,

Reference 55

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source=pdf_text observed=2026-08-04T12:45:34.378909Z digest=sha256:8bb948a16195038a4f60e3b9b38cdea110065f966e74361b55aba0dd4750c5e8

Observation 8c98bb71-1683-4bce-bfe7-5be445227e26 · outbound

This paper cites LATINO-PRO: Latent consistency inverse solver with prompt opti- mization,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems LATINO-PRO: Latent consistency inverse solver with prompt opti- mization,

Reference 56

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source=pdf_text observed=2026-08-04T12:45:34.571188Z digest=sha256:009076d96157d4735376d7559cbd3603cfa6e491d0de36092a64c19417eda487

Observation 3639c59b-d1a1-4549-849d-4e7c00147521 · outbound

This paper cites Zero-shot image restoration using few-step guidance of consistency models (and beyond),.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Zero-shot image restoration using few-step guidance of consistency models (and beyond),

Reference 57

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source=pdf_text observed=2026-08-04T12:45:34.739599Z digest=sha256:58507d80efb1cc1f3c6c7dd59bc89e7378b970cb4373d447e645b4510cb26b49

Observation 4aa33a5a-180d-4b9e-9ab1-0ba9a5fe4d98 · outbound

This paper cites DPM-Solver: A fast ODE solver for diffusion probabilistic model sampling in around 10 steps,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems DPM-Solver: A fast ODE solver for diffusion probabilistic model sampling in around 10 steps,

Reference 58

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source=pdf_text observed=2026-08-04T12:45:34.881721Z digest=sha256:cbe396bd6412336573a4d69342f9e0a23e6b27c79368281173a410063d1fbeee

Observation 409ef1b6-a87e-4ca9-a260-3c57b49e1b53 · outbound

This paper cites Elucidating the design space of diffusion-based generative models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Elucidating the design space of diffusion-based generative models,

Reference 59

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source=pdf_text observed=2026-08-04T12:45:35.100462Z digest=sha256:059f20b553310222649fc0c4fb228866008adbcfb12e8115b1fb5632a2efd2fe

Observation e7c229ee-b155-455e-be64-a73000c0738c · outbound

This paper cites The perception-distortion tradeoff,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems The perception-distortion tradeoff,

Reference 60

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source=pdf_text observed=2026-08-04T12:45:35.283748Z digest=sha256:1f524f97590a179df0817129b2db7083d7e58d8abbd066be8f2bfb1a1d157599

Observation 59d1beca-3201-41c3-81ec-593af024a7c2 · outbound

This paper cites A theory of the distortion- perception tradeoff in wasserstein space,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems A theory of the distortion- perception tradeoff in wasserstein space,

Reference 61

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source=pdf_text observed=2026-08-04T12:45:35.497482Z digest=sha256:d05a08c58d46a47c7d727633d57ac707b6aca16cbec16064b5729baeffb9320b

Observation f2783b0c-91dd-4a23-83ad-ba137b8b589c · outbound

This paper cites Looks too good to be true: An information-theoretic analysis of hallucinations in generative restoration models,.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Looks too good to be true: An information-theoretic analysis of hallucinations in generative restoration models,

Reference 62

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source=pdf_text observed=2026-08-04T12:45:35.621990Z digest=sha256:aeecc5db3006af414b297bdc7be374b215c78dd5774f7d92ff8d824097c2c1f3

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