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Paper Citation Record · LEDGER

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution

As of 9 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 1 inbound Pith citation observation for arXiv:2506.01037.

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

pith.paper-citation-record.v1
2506.01037 v1

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:56:19.162495Z

measured 76 of 76 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T19:49:46.222837Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

75 of 75 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9f00f10b-e390-4222-a235-877903fb1e7f · outbound

This paper cites Masked siamese networks for label-efficient learning.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Masked siamese networks for label-efficient learning

Reference 1

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

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Observation bbf9ac7e-42af-4848-945d-545a386a0e00 · outbound

This paper cites Vidu: a Highly Consistent, Dynamic and Skilled Text-to-Video Generator with Diffusion Models.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Vidu: a Highly Consistent, Dynamic and Skilled Text-to-Video Generator with Diffusion Models

Reference 2

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Observation 034fa7c8-621a-4c27-8b40-94772b905310 · outbound

This paper cites Video Super-Resolution Transformer.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Video Super-Resolution Transformer

Reference 3

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Observation fd6c973d-7f9c-4c9f-81c4-8b36571680bd · outbound

This paper cites Unsupervised learning of visual features by contrasting cluster assignments.Ad- vances in neural information processing systems, 33:9912– 9924, 2020.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Unsupervised learning of visual features by contrasting cluster assignments.Ad- vances in neural information processing systems, 33:9912– 9924, 2020

Reference 4

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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 bf930bbf-24db-4c9e-88b1-a4d0f559474e · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Emerg- ing properties in self-supervised vision transformers

Reference 5

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Observation 4d40e281-f844-4a06-ba60-d3efc7100567 · outbound

This paper cites Diffusart: Enhancing line art coloriza- tion with conditional diffusion models.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Diffusart: Enhancing line art coloriza- tion with conditional diffusion models

Reference 6

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Observation 744a2e8a-27ea-4e74-9eac-b9826880cea3 · outbound

This paper cites Basicvsr: The search for essential compo- nents in video super-resolution and beyond.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Basicvsr: The search for essential compo- nents in video super-resolution and beyond

Reference 7

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Observation c8dc98ce-f4a5-46df-ae20-e00fba9e025f · outbound

This paper cites Basicvsr++: Improving video super- resolution with enhanced propagation and alignment.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Basicvsr++: Improving video super- resolution with enhanced propagation and alignment

Reference 8

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Observation 96ade946-9782-48a1-91b5-3e6317809702 · outbound

This paper cites Investigating tradeoffs in real-world video super-resolution.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Investigating tradeoffs in real-world video super-resolution

Reference 9

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Observation c678cae0-9a61-4aaf-93d2-dd633e4deb32 · outbound

This paper cites Investigating tradeoffs in real-world video super-resolution.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Investigating tradeoffs in real-world video super-resolution

Reference 10

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

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Observation 08e55f1c-df77-44fe-9982-d787181fba1a · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution A simple framework for contrastive learning of visual representations

Reference 11

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

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Observation 2cbfe812-8f91-49a7-a50d-46746cf7bbc7 · outbound

This paper cites Panda-70m: Captioning 70m videos with multiple cross-modality teachers.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Panda-70m: Captioning 70m videos with multiple cross-modality teachers

Reference 12

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Observation 2c7004ce-1bf9-4d04-b75d-c5ee06bdd6da · outbound

This paper cites Image quality assessment: Unifying structure and texture similarity.IEEE transactions on pattern analysis and ma- chine intelligence, 44(5):2567–2581, 2020.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Image quality assessment: Unifying structure and texture similarity.IEEE transactions on pattern analysis and ma- chine intelligence, 44(5):2567–2581, 2020

Reference 13

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Observation 08e4bf4f-dd56-4a17-ac8f-f687dd46bd6a · outbound

This paper cites Adaptive soft contrastive learning.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Adaptive soft contrastive learning

Reference 14

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Observation 7013b0cd-e4eb-4149-a0c7-3bd7e1ebe931 · outbound

This paper cites Maskcon: Masked con- trastive learning for coarse-labelled dataset.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Maskcon: Masked con- trastive learning for coarse-labelled dataset

Reference 15

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Observation b6bbb30d-ee4d-40ae-b4b0-abe6715fe4a3 · outbound

This paper cites SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise

Reference 16

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Observation 6e27ce29-2ea3-48dd-9113-b7db7af17246 · outbound

This paper cites Self-supervised representation learning with cross-context learning between global and hypercolumn features.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Self-supervised representation learning with cross-context learning between global and hypercolumn features

Reference 17

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Observation 148f795e-4f59-4b70-ba5c-6daab419e784 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 18

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Observation 5b82160f-94bc-472c-9405-7679d9d54809 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Efficiently Modeling Long Sequences with Structured State Spaces

Reference 19

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Observation fe46dd98-d737-4676-98b7-60013c3bb5aa · outbound

This paper cites AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Reference 20

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Observation 4e3bf6c2-c51f-44f6-92fa-6adfdd164a2e · outbound

This paper cites Diagonal state spaces are as effective as structured state spaces.Advances in Neural Information Processing Systems, 35:22982–22994,.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Diagonal state spaces are as effective as structured state spaces.Advances in Neural Information Processing Systems, 35:22982–22994,

Reference 21

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Observation a97c5b24-41e1-4cb2-939c-ae5a130a1c56 · outbound

This paper cites Momentum contrast for unsupervised visual rep- resentation learning.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Momentum contrast for unsupervised visual rep- resentation learning

Reference 22

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Observation 9910dc5b-7ef2-4f60-9bc7-d5728fb04e7f · outbound

This paper cites Masked autoencoders are scalable vision learners.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Masked autoencoders are scalable vision learners

Reference 23

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Observation 65b7ebd9-6e9b-4ff2-9ed3-6637e4870e4d · outbound

This paper cites Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 24

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Observation 04ab455e-7d80-4303-b027-f15d7e9c902d · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Imagen Video: High Definition Video Generation with Diffusion Models

Reference 25

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Observation d95a4dd6-e385-432e-b431-a6a7c3d0a2d9 · outbound

This paper cites Long movie clip classification with state-space video models.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Long movie clip classification with state-space video models

Reference 26

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Observation 05b132ca-3350-47d3-bd66-e4a89549bcb6 · outbound

This paper cites Video super-resolution with recurrent structure-detail network.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Video super-resolution with recurrent structure-detail network

Reference 27

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

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Observation 782e1d3d-8e88-4fd9-955d-b03dc6ed0248 · outbound

This paper cites Video super-resolution with temporal group attention.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Video super-resolution with temporal group attention

Reference 28

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Observation 43734d44-ce6c-43d8-b085-185eca1a3953 · outbound

This paper cites Revisiting Temporal Modeling for Video Super-resolution.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Revisiting Temporal Modeling for Video Super-resolution

Reference 29

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Observation d40aa5c5-edd8-4fd6-888e-50b24542005f · outbound

This paper cites Dynamic filter networks.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Dynamic filter networks

Reference 30

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Observation 223621cb-6c2c-45aa-a991-396fd551fb62 · outbound

This paper cites Deep video super-resolution network using dynamic upsampling filters without explicit motion compen- sation.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Deep video super-resolution network using dynamic upsampling filters without explicit motion compen- sation

Reference 31

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Observation 44e25c19-ab90-41a4-9c47-2f2469fe3a27 · outbound

This paper cites A new approach to linear filtering and prediction problems.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution A new approach to linear filtering and prediction problems

Reference 32

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Observation 8aa48af0-b0f2-422f-8305-d8e8dc439693 · outbound

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

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Denoising diffusion restoration models.Advances in Neural Information Processing Systems, 35:23593–23606,

Reference 33

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Observation 18a81fa8-9fdc-4f2c-bf74-3e406f793a86 · outbound

This paper cites Imagic: Text-based real image editing with diffusion models.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Imagic: Text-based real image editing with diffusion models

Reference 34

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source=pdf_text observed=2026-08-07T11:56:19.018299Z digest=sha256:a8b0513ecfb416b9003265554ad376faf4a914b9e9585b1bfdeae6784d1ef4ce

Observation 38674a40-0290-45d6-9d8f-69d13abb8e98 · outbound

This paper cites Musiq: Multi-scale image quality transformer.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Musiq: Multi-scale image quality transformer

Reference 35

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source=pdf_text observed=2026-08-07T11:56:19.021791Z digest=sha256:edf410cfee4982432d1ae706fe26cb9344941d9003982fbcba0a3daaa5198769

Observation 03f230e9-0ed8-46c5-905f-ba60299019ac · outbound

This paper cites A method for stochastic optimization.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution A method for stochastic optimization

Reference 36

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

source=pdf_text observed=2026-08-07T11:56:19.025486Z digest=sha256:3de3109d86cdb4d42408d5f690918449f5ee755cd43923397360583300d79a87

Observation b7309f44-be06-43a5-80ac-39482b801f2d · outbound

This paper cites Open-sora-plan, 2024.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Open-sora-plan, 2024

Reference 37

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

source=pdf_text observed=2026-08-07T11:56:19.029779Z digest=sha256:dbdde87ef6452c7e89687edf2df55f3853d9d2b064a77784b6e062a87fe20fce

Observation ddd0b48b-9a92-4697-bb98-d15d1041a9ce · outbound

This paper cites Learning blind video temporal consistency.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Learning blind video temporal consistency

Reference 38

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

source=pdf_text observed=2026-08-07T11:56:19.033972Z digest=sha256:bd1bca92cfc1321a42dd4542fba449bea0f16095693db9aa892c9c78461768da

Observation a9424935-0413-47ce-867a-e7566c36f8fc · outbound

This paper cites Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data

Reference 39

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source=pdf_text observed=2026-08-07T11:56:19.037863Z digest=sha256:b37ffdf5c9b2d4637a1fc92d429ed56190223b035fe55a9134180303a07edf7a

Observation d403d388-a4a2-497d-8669-825f62bdf79a · outbound

This paper cites Mucan: Multi-correspondence aggregation net- work for video super-resolution.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Mucan: Multi-correspondence aggregation net- work for video super-resolution

Reference 40

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raw_fallback, observed 2026-08-07T11:56:19.561706Z

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=2026-08-07T11:56:19.042239Z digest=sha256:6b56d55998872d6acf064ab79f5d6275356d6f0007c86b791fd7b90f427126b7

Observation ca1c07ec-e538-4452-b756-1cb097e3f3d9 · outbound

This paper cites PointMamba: A Simple State Space Model for Point Cloud Analysis.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution PointMamba: A Simple State Space Model for Point Cloud Analysis

Reference 41

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source=pdf_text observed=2026-08-07T11:56:19.045549Z digest=sha256:97e2c4825b6c5279f6da2d170c1071d3382c33a45d2400700de145df1816d739

Observation 6bb4e000-6d37-4389-9cb9-c212f5a72f7c · outbound

This paper cites Recurrent video restoration trans- former with guided deformable attention.Advances in Neu- ral Information Processing Systems, 35:378–393, 2022.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Recurrent video restoration trans- former with guided deformable attention.Advances in Neu- ral Information Processing Systems, 35:378–393, 2022

Reference 42

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source=pdf_text observed=2026-08-07T11:56:19.049545Z digest=sha256:b88842102238187405f0dc95316a42c94475d27d738436c9b0822d42a902aa90

Observation ce7cba02-52de-42ff-bef1-2fc68aba6189 · outbound

This paper cites Vrt: A video restoration transformer.IEEE Transactions on Image Processing, 2024.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Vrt: A video restoration transformer.IEEE Transactions on Image Processing, 2024

Reference 43

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:56:19.053105Z digest=sha256:6316334cbea0caac6752d0d24e25b08b3f3cb47a5d262eadb5adb8393acdaa57

Observation 1d98475d-f21d-4495-9dfc-db6221668d82 · outbound

This paper cites On bayesian adaptive video super resolution.IEEE transactions on pattern analysis and ma- chine intelligence, 36(2):346–360, 2013.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution On bayesian adaptive video super resolution.IEEE transactions on pattern analysis and ma- chine intelligence, 36(2):346–360, 2013

Reference 44

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raw_fallback, observed 2026-08-07T11:56:19.542651Z

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=2026-08-07T11:56:19.056556Z digest=sha256:1a9150963275b27d2b4be23c7d3efbd92dd258097945f1e54ef903606acec1a3

Observation 3a07e878-1866-4710-9f0f-cfe9e9fa317f · outbound

This paper cites Repaint: Inpainting using denoising diffusion probabilistic models.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Repaint: Inpainting using denoising diffusion probabilistic models

Reference 45

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source=pdf_text observed=2026-08-07T11:56:19.060556Z digest=sha256:02be3cf7751d5c1095dd320b8259ab2c79aab542ffb30c337508eca78518d31f

Observation ef17ecad-34f4-4a34-b76b-6bdd1af0a92b · outbound

This paper cites completely blind.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution completely blind

Reference 46

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:56:19.064156Z digest=sha256:5e274b8d65467a3f74c37992724a610cd99a2fd5b6ec1e1e290c1e10dafc21cf

Observation e6091e67-fc28-4119-8761-aee7266762c1 · outbound

This paper cites Ntire 2019 challenge on video deblurring and super- resolution: Dataset and study.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Ntire 2019 challenge on video deblurring and super- resolution: Dataset and study

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:19.524146Z

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=2026-08-07T11:56:19.067602Z digest=sha256:45aba1a3b59f3d3c1588030c2a03f0a8f99355ae500503a8d35cde96140611d7

Observation 8fea2f14-4ab8-4cdc-918d-5ebf529144c9 · outbound

This paper cites S4nd: Modeling images and videos as multidimensional signals with state spaces.Advances in neural information processing systems, 35:2846–2861, 2022.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution S4nd: Modeling images and videos as multidimensional signals with state spaces.Advances in neural information processing systems, 35:2846–2861, 2022

Reference 48

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raw_fallback, observed 2026-08-07T11:56:19.514873Z

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=2026-08-07T11:56:19.070486Z digest=sha256:fb4bd66a48a8ab2b38def98d38a286d1a049c3b29abc4f0243668006a5f8538b

Observation 4a15a2d3-e629-4d84-b1e1-c5bf9d510209 · outbound

This paper cites Deep blind video super-resolution.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Deep blind video super-resolution

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-07T11:56:19.505303Z

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=2026-08-07T11:56:19.074315Z digest=sha256:d0f303a618be411d6624045b43eab4d968909812136c4c30835e017557791c72

Observation 57d1a527-e4bd-44ff-82ca-b4125f600380 · outbound

This paper cites Movie Gen: A Cast of Media Foundation Models.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Movie Gen: A Cast of Media Foundation Models

Reference 50

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source=pdf_text observed=2026-08-07T11:56:19.077238Z digest=sha256:0a8a72aff42ac3631906f956c6603a9e2cf506bdcb301eaef814e6ad605625a8

Observation f8112753-8235-4392-a3e4-1381d51fdaa4 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 51

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source=pdf_text observed=2026-08-07T11:56:19.080961Z digest=sha256:505ac067e33797dbd77bff80a1711fdf7bac3b6b5180d6d435f0d0375e1d1fe4

Observation 59e2db3e-f0e8-4533-869d-905c587388b5 · outbound

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

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution High-resolution image synthesis with latent diffusion models

Reference 52

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source=pdf_text observed=2026-08-07T11:56:19.084715Z digest=sha256:4b410b3dee29d44cd24365dac5c9e66d91440db8963e9eb0420f2cda767f4f12

Observation 2798be9a-5a35-45c8-9da8-fee00f15bd42 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep 10 language understanding.Advances in neural information processing systems, 35:36479–36494, 2022.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Photorealistic text-to-image diffusion models with deep 10 language understanding.Advances in neural information processing systems, 35:36479–36494, 2022

Reference 53

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raw_fallback, observed 2026-08-07T11:56:19.491482Z

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=2026-08-07T11:56:19.087986Z digest=sha256:366dae59f2bd1962b9328cdc1fa0d44d7b6bfb8b020c69e560ce489ee381b5c1

Observation 97c8fec1-98f3-491e-8971-6eab84adfdd6 · outbound

This paper cites Simplified State Space Layers for Sequence Modeling.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Simplified State Space Layers for Sequence Modeling

Reference 54

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source=pdf_text observed=2026-08-07T11:56:19.091847Z digest=sha256:5bc9e8dc3c117551da7073507d380451d63fa51a84d783dac3e70535248926a9

Observation 8dfc46bb-dc6a-4a71-90d9-e02d9d6d6959 · outbound

This paper cites Detail-revealing deep video super-resolution.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Detail-revealing deep video super-resolution

Reference 55

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raw_fallback, observed 2026-08-07T11:56:19.481668Z

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=2026-08-07T11:56:19.095322Z digest=sha256:6e0693b6aee9fad37f323d5c6befccb28f947180cb27e6044e296fe99eb9a32c

Observation d700ec39-fa82-4f74-807f-f48898f9028f · outbound

This paper cites Ex- ploring clip for assessing the look and feel of images.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Ex- ploring clip for assessing the look and feel of images

Reference 56

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source=pdf_text observed=2026-08-07T11:56:19.098349Z digest=sha256:0ec0d87b23ba1b549749452a5471a5b8f3014eddf8762968d1e7d5ab6b8ec024

Observation 69de7a97-542b-4022-b964-9bb34b243741 · outbound

This paper cites Selective structured state-spaces for long-form video understanding.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Selective structured state-spaces for long-form video understanding

Reference 57

Resolution
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raw_fallback, observed 2026-08-07T11:56:19.468079Z

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=2026-08-07T11:56:19.101551Z digest=sha256:ab3d08a74d5dda1e1b91122cff0d85eb7bda3bc4b76393ffa87b101ec71edb6c

Observation 75a53956-49ee-4c89-99dc-31ab2df6d8ee · outbound

This paper cites Exploiting diffusion prior for real-world image super-resolution.International Journal of Computer Vision, pages 1–21, 2024.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Exploiting diffusion prior for real-world image super-resolution.International Journal of Computer Vision, pages 1–21, 2024

Reference 58

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raw_fallback, observed 2026-08-07T11:56:19.458846Z

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=2026-08-07T11:56:19.104900Z digest=sha256:09acc31905b65ff4ee0a3918ae360b95ec355e69c3f2e3bcd7ece877ae7afd63

Observation e7d98d0b-54b0-431e-9b94-83ee8403368d · outbound

This paper cites Exploiting diffusion prior for real-world image super-resolution.International Journal of Computer Vision, pages 1–21, 2024.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Exploiting diffusion prior for real-world image super-resolution.International Journal of Computer Vision, pages 1–21, 2024

Reference 59

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raw_fallback, observed 2026-08-07T11:56:19.449176Z

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=2026-08-07T11:56:19.108188Z digest=sha256:61554d8fcf0d9c4f438d88f26f0ab53be883437fb2e66d2a02357cbc96ce1b63

Observation d4fe3596-daa3-43c2-be3f-8debe269f603 · outbound

This paper cites Edvr: Video restoration with enhanced deformable convolutional networks.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Edvr: Video restoration with enhanced deformable convolutional networks

Reference 60

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raw_fallback, observed 2026-08-07T11:56:19.440295Z

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=2026-08-07T11:56:19.111280Z digest=sha256:532e17c1c8dddfdc4a71655c17408dfaf8c3109cdfe70bd5e015d5da7167c922

Observation ea11cdb6-f5e0-41a2-a489-71bf545445bd · outbound

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

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Real-esrgan: Training real-world blind super-resolution with pure synthetic data

Reference 61

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source=pdf_text observed=2026-08-07T11:56:19.114233Z digest=sha256:66238b13f282f7a6ce075759f7f30bd40771b53aa45819ca425a80d7c4996ef9

Observation 944ced1e-847e-44df-93c3-334dc73bc601 · outbound

This paper cites Exploring video quality assessment on user gener- ated contents from aesthetic and technical perspectives.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Exploring video quality assessment on user gener- ated contents from aesthetic and technical perspectives

Reference 62

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source=pdf_text observed=2026-08-07T11:56:19.117580Z digest=sha256:11e30a193f6d91b0506bf72ddde62a07f34e09ee509da0d468bca40f785e1222

Observation 3431231e-5a09-44bd-aba1-01d4ece6f8a0 · outbound

This paper cites Mitigating artifacts in real-world video super-resolution models.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Mitigating artifacts in real-world video super-resolution models

Reference 63

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verified fuzzy
raw_fallback, observed 2026-08-07T11:56:19.421763Z

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=2026-08-07T11:56:19.120737Z digest=sha256:1e3d1df19a04b2cc029a2d18a8d6819345fc5701c11e86baa068aac6a6265bc3

Observation fe7b2e1b-71ac-45c7-8d93-faf923e973be · outbound

This paper cites Simmim: A simple framework for masked image modeling.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Simmim: A simple framework for masked image modeling

Reference 64

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no resolver link, observed 2026-08-07T11:56:19.123676Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:56:19.123676Z digest=sha256:a71c0f3979187f893f1aaaa3030a3272a2266ffe20268922a9d20c4cc406de5c

Observation f0e18d28-a00f-43b0-9f9b-c32a0a177aed · outbound

This paper cites Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation

Reference 65

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raw_fallback, observed 2026-08-07T11:56:19.407420Z

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=2026-08-07T11:56:19.126732Z digest=sha256:04e0ecae15036cb5a65eea2f08f7227742969227c8faba086d524e09b4c51816

Observation 010f26d6-032f-4b29-bab3-e1d34d55fe8f · outbound

This paper cites Video enhancement with task-oriented flow.International Journal of Computer Vision, 127:1106– 1125, 2019.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Video enhancement with task-oriented flow.International Journal of Computer Vision, 127:1106– 1125, 2019

Reference 66

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verified fuzzy
raw_fallback, observed 2026-08-07T11:56:19.397162Z

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=2026-08-07T11:56:19.130273Z digest=sha256:5bd946183c55559b20f62b0a2641dbb957b28d6473a095f07971e2db40114875

Observation a474a792-3a00-4a0d-a88b-2a6f07e2294b · outbound

This paper cites Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylization.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylization

Reference 67

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source=pdf_text observed=2026-08-07T11:56:19.133724Z digest=sha256:5e53a07b6de4c69e3bc00623efe62bbe4e0bfc19ea7e7ca9d174255dc38b4172

Observation 75a3a9f5-0702-4158-8476-2ce9929352d9 · outbound

This paper cites Real- world video super-resolution: A benchmark dataset and a de- composition based learning scheme.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Real- world video super-resolution: A benchmark dataset and a de- composition based learning scheme

Reference 68

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verified fuzzy
raw_fallback, observed 2026-08-07T11:56:19.387991Z

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=2026-08-07T11:56:19.137121Z digest=sha256:d07ec2a72055560b6429defd818a858be6b72467423621a1f504158afdaa0506

Observation 54a8545f-f868-4e66-a3f0-3bf0d5276820 · outbound

This paper cites Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolution.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolution

Reference 69

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local_arxiv, observed 2026-08-07T11:56:19.222507Z

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=2026-08-07T11:56:19.140260Z digest=sha256:c8ac1d1cfa8d4055d646d0b53ab7e2f54ba282039742d126d364c3ef48373369

Observation 35040288-4fdf-4d89-b6ae-35dc15780646 · outbound

This paper cites Progressive fusion video super-resolution network via exploiting non-local spatio-temporal correlations.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Progressive fusion video super-resolution network via exploiting non-local spatio-temporal correlations

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:19.378391Z

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 93e61fcd-4dd4-4d7d-ba6b-acccdb0185d9 · outbound

This paper cites Adding conditional control to text-to-image diffusion models, 2023.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Adding conditional control to text-to-image diffusion models, 2023

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T11:56:19.147295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:56:19.147295Z digest=sha256:b6e6a45cb3b1c0cd2cee7da3d94fe7b58f77b29871a384e84f9bfb283fc9248d

Observation 9f539182-1f0d-4ecd-abbc-9eaee0c08d32 · outbound

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

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution The unreasonable effectiveness of deep features as a perceptual metric

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-07T11:56:19.151103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:56:19.151103Z digest=sha256:89eaa7fafbeea9b951f58041d005ebd2da070f03b2de73371aa9bd0bc873fa40

Observation a8168367-a5fe-45b4-bace-999f90d27620 · outbound

This paper cites RealViformer: Investigating Attention for Real-World Video Super-Resolution.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution RealViformer: Investigating Attention for Real-World Video Super-Resolution

Reference 73

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:56:19.208043Z

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=2026-08-07T11:56:19.154589Z digest=sha256:d9e48b8f3604d120e9dbe19cea405c667aabf70b936dc5ebdb6bfe0e19e2f897

Observation 990d8255-c654-4444-b7e3-21c4e87d460d · outbound

This paper cites Upscale-a-video: Temporal- consistent diffusion model for real-world video super- resolution.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Upscale-a-video: Temporal- consistent diffusion model for real-world video super- resolution

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:56:19.357372Z

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 0fefa1b4-b97e-4d33-a412-3401a32da63a · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-07T11:56:19.162495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:56:19.162495Z digest=sha256:83aceb9ed214f4db61fb1b3b6d7d96fb4d35634f0ed2d83c379348e4e8807c8a

Pith citing papers

Observation 8f21914b-3fef-446a-a88f-f5a3a8ad87b2 · inbound

VEMamba: Efficient Isotropic Reconstruction of Volume Electron Microscopy with Axial-Lateral Consistent Mamba cites this paper.

VEMamba: Efficient Isotropic Reconstruction of Volume Electron Microscopy with Axial-Lateral Consistent Mamba Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-02T19:49:46.222837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:49:46.222837Z digest=sha256:85f5f6a5a189e9097d9e40babf44d1de4d8d8cc412812c8d21233b44c5de2873