Paper Citation Record · LEDGER

ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 29 inbound Pith citation observations for arXiv:2301.00808.

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

pith.paper-citation-record.v1
2301.00808 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 29 of 29 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:49:12.221301Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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External citation measurements

65
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b91dceb5-c17c-4cc3-a85c-e877f5730119 · inbound

Understanding Transformer-based Vision Models through Inversion cites this paper.

Understanding Transformer-based Vision Models through Inversion ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T19:39:39.211172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43e4e316-5465-4486-90eb-a56bfaa88f7a · inbound

Multilabel Classification for Lung Disease Detection: Integrating Deep Learning and Natural Language Processing cites this paper.

Multilabel Classification for Lung Disease Detection: Integrating Deep Learning and Natural Language Processing ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T15:00:06.678437Z

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Observation 0cc0fc31-a234-4730-962b-efd538e648b3 · inbound

MATCHED: Multimodal Authorship-Attribution To Combat Human Trafficking in Escort-Advertisement Data cites this paper.

MATCHED: Multimodal Authorship-Attribution To Combat Human Trafficking in Escort-Advertisement Data ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-11T12:50:12.093228Z

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Observation c71c888f-d42e-4c95-838f-d4c5db69cef3 · inbound

UNet--: Memory-Efficient and Feature-Enhanced Network Architecture based on U-Net with Reduced Skip-Connections cites this paper.

UNet--: Memory-Efficient and Feature-Enhanced Network Architecture based on U-Net with Reduced Skip-Connections ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T04:54:35.584114Z

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Observation cd65c733-f424-4f0b-8de9-0907dbd09c4b · inbound

Dedicated Inference Engine and Binary-Weight Neural Networks for Lightweight Instance Segmentation cites this paper.

Dedicated Inference Engine and Binary-Weight Neural Networks for Lightweight Instance Segmentation ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T22:26:32.640059Z

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Observation 378c1f21-a5ac-4a24-a2e1-d857524c7019 · inbound

MIM: Multi-modal Content Interest Modeling Paradigm for User Behavior Modeling cites this paper.

MIM: Multi-modal Content Interest Modeling Paradigm for User Behavior Modeling ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T19:32:18.818455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e349ed2-2c6d-4de5-9aca-a44cb211432d · inbound

RaPA: Enhancing Transferable Targeted Attacks via Random Parameter Pruning cites this paper.

RaPA: Enhancing Transferable Targeted Attacks via Random Parameter Pruning ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-22T18:41:56.447002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9c340e9d-7bb0-4343-a145-7ed149a86112 · inbound

Mahalanobis++: Improving OOD Detection via Feature Normalization cites this paper.

Mahalanobis++: Improving OOD Detection via Feature Normalization ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:24.811478Z

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Observation 2b3e19f3-5e97-427e-ade1-76425bf5ffbd · inbound

SIM-Net: A Multimodal Fusion Network Using Inferred 3D Object Shape Point Clouds from RGB Images for 2D Classification cites this paper.

SIM-Net: A Multimodal Fusion Network Using Inferred 3D Object Shape Point Clouds from RGB Images for 2D Classification ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T18:49:12.221301Z

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Observation b46d0db2-d86b-4a13-aca4-ba627ae1c8c1 · inbound

AeroLite-MDNet: Lightweight Multi-task Deviation Detection Network for UAV Landing cites this paper.

AeroLite-MDNet: Lightweight Multi-task Deviation Detection Network for UAV Landing ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T22:54:21.901862Z

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Observation d6bbc16f-a727-4250-a1f4-4c74e3d8f231 · inbound

MVGBench: Comprehensive Benchmark for Multi-view Generation Models cites this paper.

MVGBench: Comprehensive Benchmark for Multi-view Generation Models ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T04:52:09.842949Z

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Observation f0ff0cf9-3c50-4858-9037-a99cb6c6d5d9 · inbound

On the rankability of visual embeddings cites this paper.

On the rankability of visual embeddings ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T20:11:51.656002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7567e3a-c51c-4aca-94ff-18800bf341a7 · inbound

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models cites this paper.

QuarterMap: Efficient Post-Training Token Pruning for Visual State Space Models ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:31.845406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5337e5b9-e382-4e1a-ab0c-9c1b96ce9150 · inbound

Disentanglement and Assessment of Shortcuts in Ophthalmological Retinal Imaging Exams cites this paper.

Disentanglement and Assessment of Shortcuts in Ophthalmological Retinal Imaging Exams ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T17:54:52.318302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ff89682-cb2b-44f4-881e-5dc0e65bc7a4 · inbound

WaveLLDM: Design and Development of a Lightweight Latent Diffusion Model for Speech Enhancement and Restoration cites this paper.

WaveLLDM: Design and Development of a Lightweight Latent Diffusion Model for Speech Enhancement and Restoration ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-05T14:36:37.710782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b696906-5933-467b-8df1-d196df74fbf1 · inbound

Fast Feature Field ($\text{F}^3$): A Predictive Representation of Events cites this paper.

Fast Feature Field ($\text{F}^3$): A Predictive Representation of Events ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-15T15:49:18.211268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d711f93-5892-4d1c-b25f-961151d679cc · inbound

Transcoda: End-to-End Zero-Shot Optical Music Recognition via Data-Centric Synthetic Training cites this paper.

Transcoda: End-to-End Zero-Shot Optical Music Recognition via Data-Centric Synthetic Training ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:41:26.791263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a5077056-906a-4a6e-9c18-94c0b940d504 · inbound

When Does Sparse MoE Help in Vision? The Role of Backbone Compute Leverage in Sparse Routing cites this paper.

When Does Sparse MoE Help in Vision? The Role of Backbone Compute Leverage in Sparse Routing ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T16:22:39.089429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 080d9590-96bd-4fa8-a406-c0b0c1c37ce6 · inbound

Toward Calibrated, Fair, and accurate Deepfake Detection cites this paper.

Toward Calibrated, Fair, and accurate Deepfake Detection ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 84

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T07:11:45.358496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cae7ec2e-35c0-4e5c-b240-fa1d53effa90 · inbound

Fourier Features Let Agents Learn High Precision Policies with Imitation Learning cites this paper.

Fourier Features Let Agents Learn High Precision Policies with Imitation Learning ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-07-03T08:47:50.422641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ac30da71-55cc-471a-8978-be414f433c7c · inbound

Physics-Constrained Neural Networks for Improved Short-Term Weather Forecasting: A Case Study over the South Pacific cites this paper.

Physics-Constrained Neural Networks for Improved Short-Term Weather Forecasting: A Case Study over the South Pacific ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T19:28:52.809551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5288c427-5cbb-4bb3-8dbf-18cadb553a7b · inbound

Forged Calamity: Benchmark for Cross-Domain Synthetic Disaster Detection in the Age of Diffusion cites this paper.

Forged Calamity: Benchmark for Cross-Domain Synthetic Disaster Detection in the Age of Diffusion ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T23:59:07.345949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 54e90850-509c-4a3e-9424-8a4569438ab4 · inbound

Liquid Fusion of Heterogeneous Representations Towards General Salient Object Detection cites this paper.

Liquid Fusion of Heterogeneous Representations Towards General Salient Object Detection ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 67

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T12:59:52.166691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c27a1dcc-5dec-4ec5-b254-aba887f7f36d · inbound

Cross-Modal Fusion of OCT and OCT angiography enface for Improved Diagnostics of Diabetic Retinopathy cites this paper.

Cross-Modal Fusion of OCT and OCT angiography enface for Improved Diagnostics of Diabetic Retinopathy ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-11T22:45:34.273188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f596b46-9803-4a03-910d-d7e4ce14da2a · inbound

AI-guided stimuli discovery and generation to optimize facial emotion perception studies in autism cites this paper.

AI-guided stimuli discovery and generation to optimize facial emotion perception studies in autism ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-07-10T05:56:50.442376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cabea251-e2a0-4456-81cf-d9e469812438 · inbound

GenSyn10: A Multi-Generative AI Dataset For Benchmarking Image Classification cites this paper.

GenSyn10: A Multi-Generative AI Dataset For Benchmarking Image Classification ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-02T07:41:41.358271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f1a7d8f-f173-4671-b80b-e21beb226ea5 · inbound

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction cites this paper.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-30T23:02:40.103651Z

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Unavailable: canonical work link unavailable.

Observation 9d7e75ee-75c0-47c8-ba4d-d9fddb09818d · inbound

AHA-Memes: A Fine-Grained Multimodal Benchmark for Understanding Hate in Arabic Memes cites this paper.

AHA-Memes: A Fine-Grained Multimodal Benchmark for Understanding Hate in Arabic Memes ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T08:12:45.329350Z

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Unavailable: canonical work link unavailable.

Observation 9cb226fb-7b5f-4f81-b452-eecce1b3398c · inbound

LaPrune: Controllable Differentiable Sparsity at Million Scale cites this paper.

LaPrune: Controllable Differentiable Sparsity at Million Scale ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-08T00:53:24.638438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.