Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T23:43:38.914760Z
Paper Citation Record · LEDGER
As of 14 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2412.02234.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T23:43:38.914760Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
53 of 53 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 78a1919c-5e40-4101-9362-060fa99dfe30 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Fast, accurate, and lightweight super-resolution with cascading residual network
Reference 1
Source-reported events for the cited work
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Observation 1185978e-70b6-4926-b48b-ffc1129867d9 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Pre-trained image processing transformer
Reference 2
Source-reported events for the cited work
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Observation af9cd5e8-fdec-4990-8775-8b6f2fbc3d99 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Simple baselines for image restoration
Reference 3
Source-reported events for the cited work
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Observation 21acf323-dc98-4b1b-b050-371d3c30c93c · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Activating more pixels in image super- resolution transformer
Reference 4
Source-reported events for the cited work
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Observation a7f6b927-8ce4-431d-b134-c5e1c1d27aa6 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Mobile- former: Bridging mobilenet and transformer
Reference 5
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Observation 95bbe9ab-9144-47f4-a512-41640618a4ab · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Rethinking coarse-to-fine approach in sin- gle image deblurring
Reference 6
Source-reported events for the cited work
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Observation ad17187d-6f72-4eba-bbb0-c16fe02be329 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Fast, accurate and lightweight super-resolution with neural architecture search
Reference 7
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Observation 226880d2-2fc4-4745-b2ba-3af59492eb1a · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Image super-resolution using deep convolutional net- works
Reference 8
Source-reported events for the cited work
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Observation cc40d460-b826-4e9a-bd2c-90d5a5ab256b · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 9
Source-reported events for the cited work
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Observation fdc8712a-6c1f-471b-ab32-aef6dcb9ff53 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Image super-resolution using knowledge distillation
Reference 10
Source-reported events for the cited work
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Observation adf9bce6-08a3-43a7-85a6-083e909c5ab5 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Mixer-based local residual network for lightweight image super-resolution
Reference 11
Source-reported events for the cited work
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Observation 24104215-2c43-4964-b416-25bc7b60e0f8 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Distilling the Knowledge in a Neural Network
Reference 12
Source-reported events for the cited work
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Observation fc568952-31bd-49b3-881f-a414dddd4f4c · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Reference 13
Source-reported events for the cited work
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Observation 0ebcbdda-f2f1-488d-ab3c-cd930973cbc2 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Squeeze-and-excitation net- works
Reference 14
Source-reported events for the cited work
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Observation 56d54767-fc8a-43e0-bd2b-9acd755e9dab · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Sin- gle image super-resolution from transformed self-exemplars
Reference 15
Source-reported events for the cited work
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Observation a4cdb1d8-3717-4997-8c34-c3efaf0b4ed9 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution LightViT: Towards Light-Weight Convolution-Free Vision Transformers
Reference 16
Source-reported events for the cited work
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Observation 4d4be8cf-9898-428e-9c78-a3e7d9d9481c · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Fast and ac- curate single image super-resolution via information distil- lation network
Reference 17
Source-reported events for the cited work
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Observation 1399d563-2519-4f5e-ba77-da72dd10499a · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Lightweight image super-resolution with information multi- distillation network
Reference 18
Source-reported events for the cited work
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Observation c863b80b-eb09-48ff-ad53-93e0e2d1d9d6 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Accurate image super-resolution using very deep convolutional net- works
Reference 19
Source-reported events for the cited work
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Observation 8b6af5cb-1e89-489f-8d42-965b9042fa22 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Adam: A Method for Stochastic Optimization
Reference 20
Source-reported events for the cited work
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Observation d33b5524-54f2-49c9-9102-7951dc2230ac · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Residual local feature network for efficient super-resolution
Reference 21
Source-reported events for the cited work
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Observation 348ea66f-a2cc-4a85-99a6-4a333907c284 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Srconvnet: A transformer-style con- vnet for lightweight image super-resolution
Reference 22
Source-reported events for the cited work
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Observation 4943b258-7ade-440b-85d5-a3faff511e5a · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution On Efficient Transformer-Based Image Pre-training for Low-Level Vision
Reference 23
Source-reported events for the cited work
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Observation 32efea84-c7ff-4323-a74a-8e621ef5355a · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Effi- cient and explicit modelling of image hierarchies for image restoration
Reference 24
Source-reported events for the cited work
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Observation ab42e444-12b7-4aec-81c9-0869706200df · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Swinir: Image restoration us- ing swin transformer
Reference 25
Source-reported events for the cited work
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Observation 138f1ac3-92ef-46cb-9b63-d27bf48b1ec7 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Enhanced deep residual networks for sin- gle image super-resolution
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 875127f8-870a-4c51-9d94-59c980c550de · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Residual feature dis- tillation network for lightweight image super-resolution
Reference 27
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 19aa203a-1924-41a2-a596-a7a90b7daf43 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Swin transformer: Hierarchical vision transformer using shifted windows
Reference 28
Source-reported events for the cited work
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Observation d974bb70-d0bb-4906-9435-9f7a0be770e7 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Transformer for single image super-resolution
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2759b13f-36aa-4b1b-b703-f2d3de452337 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Latticenet: Towards lightweight image super-resolution with lattice block
Reference 30
Source-reported events for the cited work
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Observation ab98c3cd-51dc-4dff-8df9-b3ff4f2c21c0 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Shufflenet v2: Practical guidelines for efficient cnn architec- ture design
Reference 31
Source-reported events for the cited work
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Observation ce76d141-30ac-4b02-a14c-0100894dea72 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
Reference 32
Source-reported events for the cited work
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Observation dd758866-bf07-4a0a-9aad-0ee41d14f263 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Sketch-based manga retrieval using manga109 dataset
Reference 33
Source-reported events for the cited work
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Observation d305b1d6-dc19-49d7-bb2d-d17249dd4293 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer
Reference 34
Source-reported events for the cited work
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Observation 13f6bd5c-abfa-412a-916c-32567cf9a107 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Multi-attention based ul- tra lightweight image super-resolution
Reference 35
Source-reported events for the cited work
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Observation fabc9955-783e-4b06-bd83-5171ad805ecf · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
Reference 36
Source-reported events for the cited work
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Observation b17464ce-2a5d-4d7b-9c66-0e17c9221cc0 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Hy- brid pixel-unshuffled network for lightweight image super- resolution
Reference 37
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation ac9c5d20-154b-4a44-83dd-03718a201cca · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Shufflemixer: An efficient convnet for image super-resolution
Reference 38
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 151450d3-c7ac-47c0-afb2-3b9a234cbe77 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Spatially-adaptive feature modulation for efficient image super-resolution
Reference 39
Source-reported events for the cited work
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Observation bec208b9-8767-4d2e-a4cc-402f3e049776 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Ntire 2017 challenge on single image super-resolution: Methods and results
Reference 40
Source-reported events for the cited work
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Observation 228830c7-d47e-453d-8c93-547df28786e6 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Attention is all you need
Reference 41
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 5f0a886f-b044-4d0e-98bc-1e3c7a52280f · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Omni aggregation networks for lightweight im- age super-resolution
Reference 42
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 07dfb02c-3eb8-4d43-8ae4-e4c1e228c45b · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Global aligned structured sparsity learning for efficient image super-resolution
Reference 43
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 3e5e97e4-6068-4d9c-9778-694204230880 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Linformer: Self-Attention with Linear Complexity
Reference 44
Source-reported events for the cited work
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Observation 7265f3a0-f79c-4f97-9c74-212f4c3ae5ac · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Osffnet: Omni-stage feature fu- sion network for lightweight image super-resolution
Reference 45
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 9d60ddbc-ba0c-4ac6-9538-e0d212196204 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Image quality assessment: from error visibility to structural similarity
Reference 46
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f3f1195c-7c8c-4bfd-be69-81cdc99c1b16 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Lite vision trans- former with enhanced self-attention
Reference 47
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2df1aac6-9fec-473d-85f9-84decbf22850 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution See more details: Efficient image super- resolution by experts mining
Reference 48
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 48e1c35d-947c-4201-8b40-d84a060bbde6 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Restormer: Efficient transformer for high-resolution image restoration
Reference 49
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation a2d677f6-e14f-4949-b8d4-b2dc85593f29 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Learning deep cnn denoiser prior for image restoration
Reference 50
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 4d0ae19e-3432-488c-9599-5907bb4d74cb · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Shufflenet: An extremely efficient convolutional neural net- work for mobile devices
Reference 51
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation a4e85807-f68b-46f9-917e-f3d46574f32e · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Image super-resolution using very deep residual channel attention networks
Reference 52
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 33e28902-560c-4a53-992d-e7477caec667 · outbound
CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution Data-free knowledge dis- tillation for image super-resolution
Reference 53
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
No inbound Pith citation observations are available.