Paper Citation Record · LEDGER

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures

As of 17 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2507.23357.

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

pith.paper-citation-record.v1
2507.23357 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:51:14.747270Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

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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

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e960b0b2-0678-40a9-85da-2c01e711ebb6 · outbound

This paper cites Bert: A sentiment analysis odyssey.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Bert: A sentiment analysis odyssey

Reference 1

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Observation 20652faa-4713-4dfc-9236-5ad372d13093 · outbound

This paper cites BEiT: BERT Pre-Training of Image Transformers.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures BEiT: BERT Pre-Training of Image Transformers

Reference 2

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Observation 711c5f5e-e939-40f3-b9b4-f89bea023d55 · outbound

This paper cites Large scale gan training for high fidelity natural image synthesis, 2019.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Large scale gan training for high fidelity natural image synthesis, 2019

Reference 3

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Observation 263473b8-8639-41ed-bf36-b2d8b6b923c7 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Emerging properties in self-supervised vision transformers

Reference 4

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Observation e0fb7093-b882-47ff-b633-a0316b77ea0f · outbound

This paper cites A simple framework for contrastive learning of visual representations, 2020.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures A simple framework for contrastive learning of visual representations, 2020

Reference 5

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Observation ccefa1f0-114e-464a-b5e7-8e0fdd6c7e06 · outbound

This paper cites An empirical study of training self-supervised vision transformers.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures An empirical study of training self-supervised vision transformers

Reference 6

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Observation 029ea3a6-6b55-4671-baed-e9c3bc1a42f5 · outbound

This paper cites A comparative study between vision transformers and CNNs in digital pathology.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures A comparative study between vision transformers and CNNs in digital pathology

Reference 7

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Observation 638cca09-1c17-4a17-850e-8d3519542692 · outbound

This paper cites BERT: Pre-training of deep bidirectional trans- formers for language understanding.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures BERT: Pre-training of deep bidirectional trans- formers for language understanding

Reference 8

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This paper cites Gan vs transformer: A generative ai comparison, June 2025.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Gan vs transformer: A generative ai comparison, June 2025

Reference 9

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Observation 8e0f864a-d53c-4b3d-8b55-e7cbc53d3124 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

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Observation 1cb4ffd6-78ec-47f7-8fdf-1af7c866873f · outbound

This paper cites Generative adversarial nets.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Generative adversarial nets

Reference 11

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Source-reported events for the cited work

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Observation 19635cb2-cb0a-4f25-9674-00042f0b40ff · outbound

This paper cites Masked autoencoders are scalable vision learners.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Masked autoencoders are scalable vision learners

Reference 12

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Observation 5a34140d-2ab6-47be-a178-0bd0909040c3 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Momentum contrast for unsupervised visual representation learning

Reference 13

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Observation 6cbb7dae-c2b7-4823-93f9-6b7663f22fcc · outbound

This paper cites Deep residual learning for image recognition.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Deep residual learning for image recognition

Reference 14

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Observation 299c23a9-2ac3-4e85-9b1d-8446d0243524 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium, 2018.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Gans trained by a two time-scale update rule converge to a local nash equilibrium, 2018

Reference 15

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Observation 0f653243-f64e-4f1b-8bc3-ae8aa29b4529 · outbound

This paper cites Denoising diffusion probabilistic models, 2020.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Denoising diffusion probabilistic models, 2020

Reference 16

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Observation 14306e41-0737-4227-b47d-3526c1054e8a · outbound

This paper cites Long short-term memory.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Long short-term memory

Reference 17

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Observation 1cf4f943-244f-4609-a989-63c440943b9f · outbound

This paper cites Progressive growing of gans for improved quality, stability, and variation, 2018.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Progressive growing of gans for improved quality, stability, and variation, 2018

Reference 18

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Observation e07963d0-ca32-491d-a0d2-bbdd8d522d2e · outbound

This paper cites Big transfer (bit): General visual representation learning.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Big transfer (bit): General visual representation learning

Reference 19

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This paper cites Imagenet classification with deep convolutional neural net- works.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Imagenet classification with deep convolutional neural net- works

Reference 20

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This paper cites Efficient self-supervised vision transformers for representation learning, 2022.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Efficient self-supervised vision transformers for representation learning, 2022

Reference 21

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Observation c18b47f1-8d98-4b30-bcaf-bd5585f74019 · outbound

This paper cites Microsoft researchers win ImageNet computer vision challenge.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Microsoft researchers win ImageNet computer vision challenge

Reference 22

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Observation 5605c68b-1028-4145-abe1-e6881f6028c1 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Swin transformer: Hierarchical vision transformer using shifted windows

Reference 23

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Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures ChatGPT, 2025

Reference 24

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This paper cites Dinov2: Learning robust visual features without supervision, 2024.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Dinov2: Learning robust visual features without supervision, 2024

Reference 25

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This paper cites High-resolution image syn- thesis with latent diffusion models, 2022.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures High-resolution image syn- thesis with latent diffusion models, 2022

Reference 26

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This paper cites Emre Celebi, and Jie Yang.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Emre Celebi, and Jie Yang

Reference 27

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Observation 60ff6a0c-40f9-4596-bfa6-af93b284b796 · outbound

This paper cites Very deep convolutional networks for large-scale image recognition.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Very deep convolutional networks for large-scale image recognition

Reference 28

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Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Highway Networks

Reference 29

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This paper cites Going deeper with convolutions, 2014.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Going deeper with convolutions, 2014

Reference 30

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This paper cites Are Convolutional Neural Networks or Transformers more like human vision?.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Are Convolutional Neural Networks or Transformers more like human vision?

Reference 31

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This paper cites Attention is all you need, 06 2017.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Attention is all you need, 06 2017

Reference 32

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This paper cites Non-local neural networks.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Non-local neural networks

Reference 33

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This paper cites Scaling vision transformers.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Scaling vision transformers

Reference 34

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This paper cites Progressive augmentation of gans, 2019.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Progressive augmentation of gans, 2019

Reference 35

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This paper cites Energy-based generative adversarial network, 2017.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures Energy-based generative adversarial network, 2017

Reference 36

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Observation 3ca1db25-c80a-43a2-8acd-8f69d73e085e · outbound

This paper cites ibot: Image bert pre-training with online tokenizer, 2022.

Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures ibot: Image bert pre-training with online tokenizer, 2022

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:14.838267Z

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Pith citing papers

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