Who Cited It

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

2023 · 1,523 citations · 0 from inside this corpus

Sanghyun Woo, Shoubhik Debnath low, Ronghang Hu, Xinlei Chen low, Zhuang Liu, In So Kweon, Saining Xie

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders (2023)ConvNeXt V2: Co-designing and…Exploiting Generative AI to Scale up Intelligent Tutoring Systems (2023)Exploiting Generative AI to S…Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh… (2015)Batch Normalization: Accelera…Aggregated Residual Transformations for Deep Neural Networks (2017)Aggregated Residual Transform…
3 of 3 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
Exploiting Generative AI to Scale up Intelligent Tutoring Systems202379,071
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…201524,404
Aggregated Residual Transformations for Deep Neural Networks201712,015

Links

DOI · OpenAlex record

Topics

Domain Adaptation and Few-Shot LearningComputer Science
Advanced Neural Network ApplicationsComputer Science
Multimodal Machine Learning ApplicationsComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports7 author record(s) attached.
  • supports68 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:57+00:00.

sha256 b3024609427ad450…