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Paper Citation Record · LEDGER

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling

As of 19 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2505.12048.

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

pith.paper-citation-record.v1
2505.12048 v2

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:47:04.177386Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7b59378a-439c-4f36-99f6-a27b5e16ef5a · outbound

This paper cites Ntire 2017 challenge on single image super- resolution: Dataset and study.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Ntire 2017 challenge on single image super- resolution: Dataset and study

Reference 1

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Observation 7802d734-8aab-4f4a-9071-59505d58159e · outbound

This paper cites Denoising diffusion probabilistic models.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Denoising diffusion probabilistic models

Reference 7

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Observation c3fa0ccb-c4e9-422b-b2e2-dbea5fe8fb07 · outbound

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

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Elucidating the design space of diffusion-based generative models

Reference 10

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Observation ad4652bd-5f10-4a8f-9645-4b16603125cb · outbound

This paper cites Musiq: Multi-scale im- age quality transformer.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Musiq: Multi-scale im- age quality transformer

Reference 12

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Observation 273b9b88-5487-4a10-9704-e43074a99207 · outbound

This paper cites Swinir: Image restoration using swin transformer.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Swinir: Image restoration using swin transformer

Reference 13

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Source-reported events for the cited work

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Observation a45a0300-29ff-4497-924b-467c516d158d · outbound

This paper cites Reconstructed con- volution module based look-up tables for efficient image super-resolution.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Reconstructed con- volution module based look-up tables for efficient image super-resolution

Reference 14

Resolution
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Observation a2d9f9ff-b02c-457e-a7a2-9d4e22ccb7f9 · outbound

This paper cites completely blind.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling completely blind

Reference 16

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Observation 2d537975-fb12-44a1-b296-8a704e2ec627 · outbound

This paper cites Blind image super-resolution with rich texture-aware codebook.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Blind image super-resolution with rich texture-aware codebook

Reference 18

Resolution
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Source-reported events for the cited work

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Observation 5c1daf3d-7b26-4568-87aa-552adaa0b5ee · outbound

This paper cites A new dataset and framework for real-world blurred images super-resolution.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling A new dataset and framework for real-world blurred images super-resolution

Reference 19

Resolution
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Observation 79ce962c-8f0e-4405-ad6b-091bce151443 · outbound

This paper cites Xpsr: Cross- modal priors for diffusion-based image super-resolution.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Xpsr: Cross- modal priors for diffusion-based image super-resolution

Reference 20

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Source-reported events for the cited work

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Observation 0f1e6bae-73ae-4b9e-8940-47f074f4d938 · outbound

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

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling High-resolution image synthesis with latent diffusion models

Reference 21

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Source-reported events for the cited work

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Observation 62bce788-615f-49c3-b6f8-15a3245c4203 · outbound

This paper cites Image super-resolution via iterative refinement.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Image super-resolution via iterative refinement

Reference 22

Resolution
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Source-reported events for the cited work

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Observation ea499b9f-7ddc-4fe2-a563-eaa84adad73a · outbound

This paper cites Denoising Diffusion Implicit Models.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Denoising Diffusion Implicit Models

Reference 23

Resolution
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Observation 226408a0-4714-45cf-834b-20025e3715e3 · outbound

This paper cites A performance evaluation of loss functions for deep face recognition, computer vision.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling A performance evaluation of loss functions for deep face recognition, computer vision

Reference 24

Resolution
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Source-reported events for the cited work

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Observation 88373389-d18a-4938-9166-44c1fbffc744 · outbound

This paper cites Real-esrgan: Training real-world blind super-resolution with pure synthetic data.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Real-esrgan: Training real-world blind super-resolution with pure synthetic data

Reference 26

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2df5d1ff-7e1a-4ae5-a832-37d26813be5a · outbound

This paper cites Exploring clip for assessing the look and feel of images.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Exploring clip for assessing the look and feel of images

Reference 27

Resolution
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Source-reported events for the cited work

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Observation 5e408283-4efa-49e2-ac3c-c2979272236c · outbound

This paper cites Component divide-and-conquer for real-world image super-resolution.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Component divide-and-conquer for real-world image super-resolution

Reference 28

Resolution
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Source-reported events for the cited work

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Observation 1e1c7d9e-6119-474f-947c-a14fa91e792a · outbound

This paper cites Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels

Reference 29

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Source-reported events for the cited work

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Observation 9a4bc8f7-6cf2-4e14-9890-5b21d92e0e5e · outbound

This paper cites One-Step Effective Diffusion Network for Real-World Image Super-Resolution.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling One-Step Effective Diffusion Network for Real-World Image Super-Resolution

Reference 30

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Observation d774d6d9-24b5-4f95-b06c-22e9a893a19f · outbound

This paper cites STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolution

Reference 31

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Observation f220bc53-78db-4c05-878f-cd656b71c5c4 · outbound

This paper cites Accelerating diffusion sampling with optimized time steps.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Accelerating diffusion sampling with optimized time steps

Reference 32

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Observation a4e306d3-a422-4e5e-aae9-e42074a48efb · outbound

This paper cites Pixel-aware stable diffu- sion for realistic image super-resolution and personalized stylization.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Pixel-aware stable diffu- sion for realistic image super-resolution and personalized stylization

Reference 33

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Source-reported events for the cited work

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Observation f52d0789-f454-474f-9537-0cb59892c1e9 · outbound

This paper cites One-step diffusion with distribution matching distillation.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling One-step diffusion with distribution matching distillation

Reference 34

Resolution
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Source-reported events for the cited work

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Observation c4c33471-c7db-4585-964f-9876220e4f52 · outbound

This paper cites Scaling up to excellence: Practicing model scaling for photo-realistic image restoration in the wild.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Scaling up to excellence: Practicing model scaling for photo-realistic image restoration in the wild

Reference 35

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Source-reported events for the cited work

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Observation 5bfb23b2-0cd7-4d24-b1c4-eb29b72d479b · outbound

This paper cites Resshift: Efficient diffusion model for image super-resolution by residual shifting.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Resshift: Efficient diffusion model for image super-resolution by residual shifting

Reference 36

Resolution
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Source-reported events for the cited work

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Observation 88ba8cfe-7205-4651-acf4-3cef8cf66378 · outbound

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

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling The unreasonable effectiveness of deep features as a perceptual metric

Reference 37

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Observation 4ef0294f-8b8e-45d7-bbe1-7d94a6b31d9b · outbound

This paper cites Adding conditional control to text-to-image dif- fusion models.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Adding conditional control to text-to-image dif- fusion models

Reference 39

Resolution
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Source-reported events for the cited work

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Observation a8570b76-5e0f-4ef6-9822-f5dbc689246c · outbound

This paper cites Quality-aware pre-trained mod- els for blind image quality assessment.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Quality-aware pre-trained mod- els for blind image quality assessment

Reference 40

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 029ac9b4-f730-4985-97da-8da4886ca383 · outbound

This paper cites Unipc: A unified predictor- corrector framework for fast sampling of diffusion mod- els.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Unipc: A unified predictor- corrector framework for fast sampling of diffusion mod- els

Reference 41

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 630a6a59-cc19-41d8-8a12-9b7c435ada6d · outbound

This paper cites DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization

Reference 42

Resolution
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Source-reported events for the cited work

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Observation 9da62946-6b48-4bd9-89bf-702f6c224229 · outbound

This paper cites One Step Diffusion-based Super-Resolution with Time-Aware Distillation.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling One Step Diffusion-based Super-Resolution with Time-Aware Distillation

Reference 1967

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e3c163bf-aa27-44ee-a5a0-cde79bd9bf7f · outbound

This paper cites Real-world super- resolution via kernel estimation and noise injection.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Real-world super- resolution via kernel estimation and noise injection

Reference 2010

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b5a173ec-6dde-4aaa-b6cc-3b5b8250448f · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 2013

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 150f1654-78b2-4d69-a9b5-2f008349e660 · outbound

This paper cites Plug-and-play tri-branch invertible block for image rescaling.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Plug-and-play tri-branch invertible block for image rescaling

Reference 2017

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3784e1dc-8753-4275-bdd4-3854817c391d · outbound

This paper cites Designing a practical degradation model for deep blind image super-resolution.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Designing a practical degradation model for deep blind image super-resolution

Reference 2018

Resolution
verified fuzzy
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation bfbbac45-ef23-4f63-9605-6a38d29f161b · outbound

This paper cites Bovik, H.R.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Bovik, H.R

Reference 2019

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b7ce7638-4035-45d9-88de-1c0802d2e4f3 · outbound

This paper cites Im- age quality metrics: Psnr vs.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Im- age quality metrics: Psnr vs

Reference 2020

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 06d9ef78-ceee-45d4-a750-05eba97df3f3 · outbound

This paper cites Cochran, J.W.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Cochran, J.W

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:47:04.848072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d2e265bf-9b4f-4095-af31-04d96de37a27 · outbound

This paper cites Denoising diffusion restora- tion models.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Denoising diffusion restora- tion models

Reference 2022

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f8fd3369-e964-4cee-a699-a01124921d1a · outbound

This paper cites Deepcache: Accelerating diffusion models for free.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling Deepcache: Accelerating diffusion models for free

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:47:04.705277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 65800cac-ca4c-4454-9375-03666931fafb · outbound

This paper cites ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-15T20:47:03.951253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 65feccea-86c9-4bea-8f05-5465e6f685d2 · outbound

This paper cites CasSR: Activating Image Power for Real-World Image Super-Resolution.

Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling CasSR: Activating Image Power for Real-World Image Super-Resolution

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-15T20:47:03.944656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.