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Paper Citation Record · LEDGER

Exploring Scalable Unified Modeling for General Low-Level Vision

As of 9 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 0 inbound Pith citation observations for arXiv:2507.14801.

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

pith.paper-citation-record.v1
2507.14801 v1

Coverage vector

measured 67 of 67 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:53:47.609817Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

67 of 67 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8fbae9a7-3652-4a9e-9a97-9c7512a89a96 · outbound

This paper cites Ai in photography: Scrutinizing implementation of super- resolution techniques in photo-editors,.

Exploring Scalable Unified Modeling for General Low-Level Vision Ai in photography: Scrutinizing implementation of super- resolution techniques in photo-editors,

Reference 1

Resolution
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Observation 9019dbdf-5701-4a49-b361-c1420b184081 · outbound

This paper cites Cardiac image super-resolution with global correspondence using multi-atlas patchmatch,.

Exploring Scalable Unified Modeling for General Low-Level Vision Cardiac image super-resolution with global correspondence using multi-atlas patchmatch,

Reference 2

Resolution
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Observation d028d7d0-39e4-4a78-87a9-e66d28cd96d3 · outbound

This paper cites Sar image despeckling through convolutional neural networks,.

Exploring Scalable Unified Modeling for General Low-Level Vision Sar image despeckling through convolutional neural networks,

Reference 3

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Observation a8464769-2104-4993-bdd0-7865c78b75d7 · outbound

This paper cites Visual prompt tuning,.

Exploring Scalable Unified Modeling for General Low-Level Vision Visual prompt tuning,

Reference 4

Resolution
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Observation b6e8d8f7-6516-4560-921f-bf025e352cf6 · outbound

This paper cites Sequential modeling enables scalable learning for large vision models,.

Exploring Scalable Unified Modeling for General Low-Level Vision Sequential modeling enables scalable learning for large vision models,

Reference 5

Resolution
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Observation 6388b217-c621-4d82-a1dd-dd5561d09af2 · outbound

This paper cites All-in-one image restoration for unknown corruption,.

Exploring Scalable Unified Modeling for General Low-Level Vision All-in-one image restoration for unknown corruption,

Reference 6

Resolution
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Observation d1e6b649-68ed-4278-aff4-ccc89e25e0d9 · outbound

This paper cites Promptir: Prompting for all-in-one image restoration,.

Exploring Scalable Unified Modeling for General Low-Level Vision Promptir: Prompting for all-in-one image restoration,

Reference 7

Resolution
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Source-reported events for the cited work

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Observation 8cb91b2b-6d15-4e81-92cb-bd75d5f319d3 · outbound

This paper cites Visual prompting via image inpainting,.

Exploring Scalable Unified Modeling for General Low-Level Vision Visual prompting via image inpainting,

Reference 8

Resolution
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Source-reported events for the cited work

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Observation 8baa3431-879c-495b-8769-86d971854d18 · outbound

This paper cites Images speak in images: A generalist painter for in-context visual learning,.

Exploring Scalable Unified Modeling for General Low-Level Vision Images speak in images: A generalist painter for in-context visual learning,

Reference 9

Resolution
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Observation 55510b9e-dd04-4498-a693-0dc2f3b4028e · outbound

This paper cites Unifying image processing as visual prompting question answering,.

Exploring Scalable Unified Modeling for General Low-Level Vision Unifying image processing as visual prompting question answering,

Reference 10

Resolution
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Source-reported events for the cited work

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Observation 8b5b0e26-9c89-43cf-94fa-b0a2301748de · outbound

This paper cites Learning a low-level vision generalist via visual task prompt,.

Exploring Scalable Unified Modeling for General Low-Level Vision Learning a low-level vision generalist via visual task prompt,

Reference 11

Resolution
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Source-reported events for the cited work

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Observation 26ecb2ce-36ce-4e99-b0e7-82f7aef42918 · outbound

This paper cites Learning a deep convolutional network for image super-resolution,.

Exploring Scalable Unified Modeling for General Low-Level Vision Learning a deep convolutional network for image super-resolution,

Reference 12

Resolution
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Source-reported events for the cited work

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Observation f7efc61f-c357-4006-93f5-3d83bbcd4018 · outbound

This paper cites Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising,.

Exploring Scalable Unified Modeling for General Low-Level Vision Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising,

Reference 13

Resolution
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Source-reported events for the cited work

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Observation e01da6e0-3d4e-4711-93c3-96a8eff1149f · outbound

This paper cites Defocus deblurring using dual-pixel data,.

Exploring Scalable Unified Modeling for General Low-Level Vision Defocus deblurring using dual-pixel data,

Reference 14

Resolution
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Source-reported events for the cited work

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Observation b4d98b22-2d32-4f12-80c7-7b4be437d898 · outbound

This paper cites Compression artifacts reduction by a deep convolutional network,.

Exploring Scalable Unified Modeling for General Low-Level Vision Compression artifacts reduction by a deep convolutional network,

Reference 15

Resolution
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Source-reported events for the cited work

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Observation 563372fd-5a3f-410d-b814-c3446aff21f1 · outbound

This paper cites Deep joint rain detection and removal from a single image,.

Exploring Scalable Unified Modeling for General Low-Level Vision Deep joint rain detection and removal from a single image,

Reference 16

Resolution
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Source-reported events for the cited work

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Observation 0feb9b8a-6d56-4d13-bc0e-55397fee96ee · outbound

This paper cites Deep joint rain detection and removal from a single image,.

Exploring Scalable Unified Modeling for General Low-Level Vision Deep joint rain detection and removal from a single image,

Reference 17

Resolution
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Source-reported events for the cited work

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Observation 3ff4ba56-84d7-4c13-be75-25d21f2e2685 · outbound

This paper cites A comprehensive overview of image enhancement techniques,.

Exploring Scalable Unified Modeling for General Low-Level Vision A comprehensive overview of image enhancement techniques,

Reference 18

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Source-reported events for the cited work

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Observation 52dc3f6f-bec8-4735-9fc4-1f52c7e17b91 · outbound

This paper cites Deep bilateral learning for real-time image enhancement,.

Exploring Scalable Unified Modeling for General Low-Level Vision Deep bilateral learning for real-time image enhancement,

Reference 19

Resolution
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Source-reported events for the cited work

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Observation 0ab3fff6-3ab4-4772-b85d-a589753f50d3 · outbound

This paper cites Fast local laplacian filters: Theory and applications,.

Exploring Scalable Unified Modeling for General Low-Level Vision Fast local laplacian filters: Theory and applications,

Reference 20

Resolution
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Source-reported events for the cited work

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Observation 451abda9-dbbd-4681-8e9f-57a9282bca68 · outbound

This paper cites Hdrunet: Single image hdr reconstruction with denoising and dequantization,.

Exploring Scalable Unified Modeling for General Low-Level Vision Hdrunet: Single image hdr reconstruction with denoising and dequantization,

Reference 21

Resolution
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Source-reported events for the cited work

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Observation 33604422-3383-4778-b4be-d130b4a927bd · outbound

This paper cites Learning to see in the dark,.

Exploring Scalable Unified Modeling for General Low-Level Vision Learning to see in the dark,

Reference 22

Resolution
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Source-reported events for the cited work

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Observation dbcb733d-46ad-4caf-ac7e-08624625e362 · outbound

This paper cites A computational approach to edge detection,.

Exploring Scalable Unified Modeling for General Low-Level Vision A computational approach to edge detection,

Reference 23

Resolution
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Source-reported events for the cited work

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Observation 2ee718c1-20b3-4984-8aa3-09c9b31420c0 · outbound

This paper cites Perceptual losses for real-time style transfer and super-resolution,.

Exploring Scalable Unified Modeling for General Low-Level Vision Perceptual losses for real-time style transfer and super-resolution,

Reference 24

Resolution
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Source-reported events for the cited work

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Observation 66d631e2-9a07-46db-9a1a-7e08704c1b04 · outbound

This paper cites Language models are few-shot learners,.

Exploring Scalable Unified Modeling for General Low-Level Vision Language models are few-shot learners,

Reference 25

Resolution
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Source-reported events for the cited work

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Observation d113340c-0bde-4b0d-ba8d-54920133b65e · outbound

This paper cites The power of scale for parameter-efficient prompt tuning,.

Exploring Scalable Unified Modeling for General Low-Level Vision The power of scale for parameter-efficient prompt tuning,

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1d067692-8ef5-4ccd-a544-95696d212ae7 · outbound

This paper cites Lora: Low-rank adaptation of large language models,.

Exploring Scalable Unified Modeling for General Low-Level Vision Lora: Low-rank adaptation of large language models,

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 9563b417-6423-47ca-8b47-db7f4ff3aaa5 · outbound

This paper cites Learning to prompt for vision- language models,.

Exploring Scalable Unified Modeling for General Low-Level Vision Learning to prompt for vision- language models,

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ccc1ab6c-2802-4f73-ade5-5e745c951df9 · outbound

This paper cites A Preliminary Exploration Towards General Image Restoration.

Exploring Scalable Unified Modeling for General Low-Level Vision A Preliminary Exploration Towards General Image Restoration

Reference 29

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Source-reported events for the cited work

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Observation 6c610707-8a14-4240-b38f-a12a47048006 · outbound

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

Exploring Scalable Unified Modeling for General Low-Level Vision Designing a practical degradation model for deep blind image super-resolution,

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e9bc7a8f-eb8f-4b9a-bfaf-cc55ff19950b · outbound

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

Exploring Scalable Unified Modeling for General Low-Level Vision Real-esrgan: Training real-world blind super-resolution with pure synthetic data,

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 28d9d293-cc86-4bef-971c-4a86a218dc17 · outbound

This paper cites Unsu- pervised degradation representation learning for blind super-resolution,.

Exploring Scalable Unified Modeling for General Low-Level Vision Unsu- pervised degradation representation learning for blind super-resolution,

Reference 32

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f742de80-0f1c-46a1-9b4e-28b0a1147e38 · outbound

This paper cites ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration.

Exploring Scalable Unified Modeling for General Low-Level Vision ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration

Reference 33

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a0287109-aa69-4252-8cbc-6ef3be0c50b5 · outbound

This paper cites A comparative study of image restoration networks for general backbone network design,.

Exploring Scalable Unified Modeling for General Low-Level Vision A comparative study of image restoration networks for general backbone network design,

Reference 34

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d7b5eefb-0d8a-4004-b306-3d47f72e915e · outbound

This paper cites Restormer: Efficient transformer for high-resolution image restoration,.

Exploring Scalable Unified Modeling for General Low-Level Vision Restormer: Efficient transformer for high-resolution image restoration,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:54.146935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:45.400298Z digest=sha256:efdcec792a551b8f1cb1ac2ce7a4bb2c87a13a75112535a84f7100b8707545ce

Observation d2c1b977-e00f-4c8c-bc49-10b0e0ffa821 · outbound

This paper cites Activating more pixels in image super-resolution transformer,.

Exploring Scalable Unified Modeling for General Low-Level Vision Activating more pixels in image super-resolution transformer,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:53.889181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:45.468538Z digest=sha256:51706c3086657c51ace3fcc2ecebb49484ddb2636793cead10a795cca8049551

Observation ea1916df-f94b-45ea-8f5f-d4420a9fd973 · outbound

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

Exploring Scalable Unified Modeling for General Low-Level Vision High-resolution image synthesis with latent diffusion models,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:53.621468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:45.527741Z digest=sha256:88712284d6eefe5c3bc50d227994298032c7728f52ba5cf9d97d180b95ca835b

Observation def46a4b-7c81-4289-ac24-0c11a0ecd693 · outbound

This paper cites Bayesian-based iterative method of image restora- tion,.

Exploring Scalable Unified Modeling for General Low-Level Vision Bayesian-based iterative method of image restora- tion,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:53.466583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:45.585189Z digest=sha256:1a71d9fa603824e2dde5d78cd56c674cdf6197eee8b4564dc202ef5bb7e8d5b6

Observation 53ebd618-20da-4d6c-9956-73b9422a373c · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Exploring Scalable Unified Modeling for General Low-Level Vision Imagenet: A large-scale hierarchical image database,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:53.174359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:45.653281Z digest=sha256:1744a040f70349043a7740486c39f12d17333a0a581fdeada4b7f3d9e03fe3b0

Observation 6ee7c35e-405f-4707-9e4b-41a44dbc955d · outbound

This paper cites Benchmarking single-image dehazing and beyond,.

Exploring Scalable Unified Modeling for General Low-Level Vision Benchmarking single-image dehazing and beyond,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:52.959737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:45.724002Z digest=sha256:c45a67eddd7640aa5d235fb84f7d7fb88458689129a0069e36298e570d6e3495

Observation d60817de-0d12-4e21-9f2f-2522f163853e · outbound

This paper cites Multi-scale progressive fusion network for single image deraining,.

Exploring Scalable Unified Modeling for General Low-Level Vision Multi-scale progressive fusion network for single image deraining,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:52.788949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:45.787387Z digest=sha256:1b0a8614006b92f9833df057eb2580cbbf85df0b09110e8b81dc0972c053caf0

Observation b498a5ea-4562-4530-afe8-3a4afccad1bf · outbound

This paper cites Edge-preserving decompositions for multi-scale tone and detail manipulation,.

Exploring Scalable Unified Modeling for General Low-Level Vision Edge-preserving decompositions for multi-scale tone and detail manipulation,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:52.548626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:45.874508Z digest=sha256:a1abf4e415d708dfcc521561aeea0c7d8d0cd80dc3a46d02a275a70cf423a6d5

Observation 59805a9d-93cf-4517-b3ed-6028ccc5da3a · outbound

This paper cites A new journey from sdrtv to hdrtv,.

Exploring Scalable Unified Modeling for General Low-Level Vision A new journey from sdrtv to hdrtv,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:52.368658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:45.940498Z digest=sha256:5cccb94dadc55f3e35590e688b1f80a9211d1c709ed108dc14978b5e3f9d137a

Observation 3ee46ffa-eb28-4839-9991-ccfddc05cf4a · outbound

This paper cites Deep retinex decomposition for low-light enhancement,.

Exploring Scalable Unified Modeling for General Low-Level Vision Deep retinex decomposition for low-light enhancement,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:52.052975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.010818Z digest=sha256:3cc63533c908ea01bf11a3b47d1bbb23a14368a7b8350dc8b0edfe663ce0d46f

Observation 518c849b-6010-4974-81c9-2725049fdd00 · outbound

This paper cites Learning photo- graphic global tonal adjustment with a database of input/output image pairs,.

Exploring Scalable Unified Modeling for General Low-Level Vision Learning photo- graphic global tonal adjustment with a database of input/output image pairs,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:51.919877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.074632Z digest=sha256:8b0dd7a43dc0149303b4e2712481d86776e8404c0dd77df203972b1acb6a85ae

Observation e2ca3251-ae53-415b-a7df-a0e7ee18c034 · outbound

This paper cites An underwater image enhancement benchmark dataset and beyond,.

Exploring Scalable Unified Modeling for General Low-Level Vision An underwater image enhancement benchmark dataset and beyond,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:51.641874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.172524Z digest=sha256:439bdf14d1a248075c2d36b3adb3e597038170b17062362d9148f8bcccbc4042

Observation de5f3077-73c0-4347-a407-37098dca7277 · outbound

This paper cites Dense extreme inception network: Towards a robust cnn model for edge detection,.

Exploring Scalable Unified Modeling for General Low-Level Vision Dense extreme inception network: Towards a robust cnn model for edge detection,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:51.380556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.249163Z digest=sha256:c17bbe3d5e1748f06e364ad7e38bf57acf22571dd58be287c820195244655f83

Observation 88a8eb0c-d586-41ed-a8bf-0a64fd40f80d · outbound

This paper cites The opencv library,.

Exploring Scalable Unified Modeling for General Low-Level Vision The opencv library,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:51.162367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.306169Z digest=sha256:6c63126e08c255724a49144c59b25f17e291806b6fd7188b7dde90cdab0f7b85

Observation 6c0ebb19-27f8-46f9-9e9c-cc1d672ae9a5 · outbound

This paper cites Combining sketch and tone for pencil drawing production,.

Exploring Scalable Unified Modeling for General Low-Level Vision Combining sketch and tone for pencil drawing production,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:51.026925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.366716Z digest=sha256:4a3a9b185e637b01683739621a39d1af708b69c8789ae526cef7f07db20b0d30

Observation ec11be61-f0cd-48ce-89cb-fbd8c07240fb · outbound

This paper cites Structure extraction from texture via relative total variation,.

Exploring Scalable Unified Modeling for General Low-Level Vision Structure extraction from texture via relative total variation,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:50.803658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.449888Z digest=sha256:6340823c5898d0292e11e3da73c9bec9bd4805c6989774b6fdeaaab661c2a12a

Observation d8f9295b-ba17-4cdc-bbbb-e18f63649b51 · outbound

This paper cites Adaattn: Revisit attention mechanism in arbitrary neural style transfer,.

Exploring Scalable Unified Modeling for General Low-Level Vision Adaattn: Revisit attention mechanism in arbitrary neural style transfer,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:50.596358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.520431Z digest=sha256:fd53b405d9e8048467ca9024c88c5adfe093e41c80d59e515cf27ee959f82e7a

Observation 8bc2f95e-4e43-4345-9468-962216d9b9a5 · outbound

This paper cites Sars-cov- 2 ct-scan dataset: A large dataset of real patients ct scans for sars-cov-2 identification,.

Exploring Scalable Unified Modeling for General Low-Level Vision Sars-cov- 2 ct-scan dataset: A large dataset of real patients ct scans for sars-cov-2 identification,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:50.378586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.600109Z digest=sha256:ea86eea05b5a50a78f191da7d5b6826e80ead51a16be051733f2286bac332cfb

Observation 82d7acd1-2d61-43ff-a294-165933badd1c · outbound

This paper cites Aid: A benchmark data set for performance evaluation of aerial scene classification,.

Exploring Scalable Unified Modeling for General Low-Level Vision Aid: A benchmark data set for performance evaluation of aerial scene classification,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:50.108112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.656292Z digest=sha256:4223b56e5f86d1c188b4071a33858692c8d73ec66cbe0c5e65fdbe1ad2025133

Observation 78134c59-2f9a-4b66-87c2-92f305ae98c0 · outbound

This paper cites Superbench: A super-resolution benchmark dataset for scientific machine learning,.

Exploring Scalable Unified Modeling for General Low-Level Vision Superbench: A super-resolution benchmark dataset for scientific machine learning,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:49.903534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.706929Z digest=sha256:4f1fdcc000d8e85b3d63531644ededc4e90ca15bc00e350227ed777fd66571ca

Observation 436b7c37-bf83-412e-b3f1-b1ab0283dfc0 · outbound

This paper cites Rellisur: A real low- light image super-resolution dataset,.

Exploring Scalable Unified Modeling for General Low-Level Vision Rellisur: A real low- light image super-resolution dataset,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:49.718301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.763706Z digest=sha256:0b62ad9c8f04c7d7eab93a9f124f84dc3166856168a84a75356894ceef3eba4b

Observation 1247f186-5305-4c62-834f-2107c5476f5f · outbound

This paper cites Seal: A framework for systematic evaluation of real-world super- resolution,.

Exploring Scalable Unified Modeling for General Low-Level Vision Seal: A framework for systematic evaluation of real-world super- resolution,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:49.490497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.820291Z digest=sha256:3e27298d70ddbbbe502627b89fd1c8930995c0aa567baff8cfb40d4f25b7a3f8

Observation 3ad052ed-0508-497e-b52a-555729731cb7 · outbound

This paper cites Toward convolutional blind denoising of real photographs,.

Exploring Scalable Unified Modeling for General Low-Level Vision Toward convolutional blind denoising of real photographs,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:49.289662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.903620Z digest=sha256:48cfcb69bf58f382d2e0935b2d5e51f164e5f13e5e3ea224f3edae16480e6fb3

Observation d1162a9e-08da-422d-8ecd-5100a16025e0 · outbound

This paper cites Real-world blur dataset for learning and benchmarking deblurring algorithms,.

Exploring Scalable Unified Modeling for General Low-Level Vision Real-world blur dataset for learning and benchmarking deblurring algorithms,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:49.140104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:46.972267Z digest=sha256:8c528a96125ad88b331971006e01eab213bf4fee497119e53217db75f4f95b1f

Observation 4cfc27dc-3af9-4d18-9bc2-d83ccef9cba6 · outbound

This paper cites Multi-stage progressive image restoration,.

Exploring Scalable Unified Modeling for General Low-Level Vision Multi-stage progressive image restoration,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:48.998828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:47.047955Z digest=sha256:d73dff19508d41c60a416c7277875d9707d59dd66a83b0dae5e22319c2e6d9bc

Observation 6d372725-19d9-4a21-975e-50983f4a0d45 · outbound

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

Exploring Scalable Unified Modeling for General Low-Level Vision Ntire 2017 challenge on single image super-resolution: Dataset and study,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:48.832764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:47.117241Z digest=sha256:a5b2ae603a72e9f27cb4804ccc29214ce565b126f13b1dbf0787ca590dca9292

Observation 9cf63c1b-3292-4d56-b4d2-a1ce0c3439ff · outbound

This paper cites Aid: A benchmark data set for performance evaluation of aerial scene classification,.

Exploring Scalable Unified Modeling for General Low-Level Vision Aid: A benchmark data set for performance evaluation of aerial scene classification,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:48.686378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:47.174899Z digest=sha256:557aa81b8ddd93c8db930b2ed620f97e8e76b03baa4cc3f65de9e36b747ee2ff

Observation 8a3e240d-e1ad-4006-b8cf-f1544bff6e36 · outbound

This paper cites Continuous remote sensing image super-resolution based on context interaction in implicit function space,.

Exploring Scalable Unified Modeling for General Low-Level Vision Continuous remote sensing image super-resolution based on context interaction in implicit function space,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:48.560945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:47.244807Z digest=sha256:6acb979112d9507a2b67c068da0c320a02b2c1d778d2646bdddcc25003b6c336

Observation fa1de669-6c2c-4087-813c-3e1d7ce336fd · outbound

This paper cites Discovering Distinctive "Semantics" in Super-Resolution Networks.

Exploring Scalable Unified Modeling for General Low-Level Vision Discovering Distinctive "Semantics" in Super-Resolution Networks

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:53:47.971367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:47.319145Z digest=sha256:5666239864a95ff2523905a596d5b05202730badc8384fdc4fdde4ffd4775bde

Observation c67ef59d-55f9-4d5d-9388-11ae5f7515da · outbound

This paper cites Revisiting the generalization problem of low-level vision models through the lens of image deraining,.

Exploring Scalable Unified Modeling for General Low-Level Vision Revisiting the generalization problem of low-level vision models through the lens of image deraining,

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T15:53:47.389687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:53:47.389687Z digest=sha256:c8e1aeec3a7ba53f130116ac1c1fee578487678b98d01bbd0571b77828428d1b

Observation 183cf5ad-84bb-46e5-9951-9c2f4c220850 · outbound

This paper cites Restoreagent: Autonomous image restoration agent via multimodal large language models,.

Exploring Scalable Unified Modeling for General Low-Level Vision Restoreagent: Autonomous image restoration agent via multimodal large language models,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:48.408530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:47.465646Z digest=sha256:2d144fe7c041bb9705fdcad94bf923234e05c40b1ca3e56645ee4abf9509fe8f

Observation 2e856d11-04f7-483a-8dbf-278ef230c474 · outbound

This paper cites Promptfix: You prompt and we fix the photo,.

Exploring Scalable Unified Modeling for General Low-Level Vision Promptfix: You prompt and we fix the photo,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:48.248187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:47.538864Z digest=sha256:f5b7b85c97aa4d1085cad569650c06edbdce6d9a345b6893653bf345276bb38b

Observation 5c1dff46-a606-4656-a43d-f121082486ec · outbound

This paper cites Pixwizard: Versatile image-to-image visual assistant with open-language instructions,.

Exploring Scalable Unified Modeling for General Low-Level Vision Pixwizard: Versatile image-to-image visual assistant with open-language instructions,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:53:48.128984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:53:47.609817Z digest=sha256:839a79038a286d9373edf52f8b229582c1611115d7d648569060e88ecfffd216

Pith citing papers

No inbound Pith citation observations are available.