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Paper Citation Record · LEDGER

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods

As of 14 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2411.11376.

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

pith.paper-citation-record.v1
2411.11376 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:37:26.615011Z

measured 46 of 46 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.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

46 of 46 outbound references displayed

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External citation measurements

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Outbound references

Observation 3c48b571-25ad-4dfd-9284-437f1a589779 · outbound

This paper cites COVID-19 Image Data Collection.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods COVID-19 Image Data Collection

Reference 1

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Observation 1cd51994-5375-4984-9171-9b7bab31a939 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale, 2021.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods An image is worth 16x16 words: Transformers for image recognition at scale, 2021

Reference 2

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Observation 8d7587e3-67ad-4505-bb44-f8e1a1a65c3f · outbound

This paper cites Mong, Safwan S.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Mong, Safwan S

Reference 3

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Observation 350b10ca-89b5-4436-8cfc-7125c4c16400 · outbound

This paper cites Bejnordi, Arnaud A.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Bejnordi, Arnaud A

Reference 4

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Observation a9dc601c-0f64-4124-b4ad-f6b80c1b2581 · outbound

This paper cites Decoupled weight decay regularization, 2019.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Decoupled weight decay regularization, 2019

Reference 5

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Observation a73843b4-041c-45f8-9405-91d45a46a0d0 · outbound

This paper cites Lungren, and Andrew Y.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Lungren, and Andrew Y

Reference 6

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Observation a6e385f0-f9ef-4c0b-91e1-234767f6858e · outbound

This paper cites Sam 2: Segment anything in images and videos, 2024.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Sam 2: Segment anything in images and videos, 2024

Reference 7

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Observation ca967dfa-2449-4431-89af-27cbdb7c5961 · outbound

This paper cites Sze-To, A.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Sze-To, A

Reference 8

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Observation 1a47044e-e54f-4ece-9590-96cd8a1b07b8 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 9

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Unresolved cited work

Reference 10

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This paper cites Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases

Reference 11

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This paper cites Language models are few-shot learners,.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Language models are few-shot learners,

Reference 12

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This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 13

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This paper cites Energy and Policy Considerations for Deep Learning in NLP.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Energy and Policy Considerations for Deep Learning in NLP

Reference 14

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This paper cites Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

Reference 15

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This paper cites Quantization and training of neural networks for efficient integer-arithmetic-only inference,.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Quantization and training of neural networks for efficient integer-arithmetic-only inference,

Reference 16

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Efficient processing of deep neural networks: A tutorial and survey,

Reference 17

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Emergent abilities of large language models,

Reference 18

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This paper cites MobileBERT: a compact task-agnostic BERT for resource-limited devices,.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods MobileBERT: a compact task-agnostic BERT for resource-limited devices,

Reference 19

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This paper cites Internet of Things (IoT) connected devices installed base worldwide from 2015 to 2025,.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Internet of Things (IoT) connected devices installed base worldwide from 2015 to 2025,

Reference 20

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Edge intelligence: Paving the last mile of artificial intelligence with edge computing,

Reference 21

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Deep learning with edge computing: A review,

Reference 22

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This paper cites Cloud-based or on-device: An empirical study of mobile deep inference,.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Cloud-based or on-device: An empirical study of mobile deep inference,

Reference 23

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Once-for-All: Train One Network and Specialize it for Efficient Deployment

Reference 24

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Reference 25

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 26

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods VeRA: Vector-based Random Matrix Adaptation

Reference 27

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Movement Pruning: Adaptive Sparsity by Fine-Tuning

Reference 28

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 29

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 30

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Vertex models for Canonical Grothendieck polynomials and their duals

Reference 31

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Thiols in the ISM: first detection of HC(O)SH and confirmation of C$_2$H$_5$SH

Reference 32

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Quantizing deep convolutional networks for efficient inference: A whitepaper

Reference 33

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Block Pruning For Faster Transformers

Reference 34

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods MnasNet: Platform-Aware Neural Architecture Search for Mobile

Reference 35

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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Overcoming catastrophic forgetting in neural networks,

Reference 36

Resolution
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raw_fallback, observed 2026-08-12T18:37:26.959863Z

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.

source=arxiv_source observed=2026-08-12T18:37:26.574971Z digest=sha256:dbf0487b2e1efae70f4dd60489c4f9a389f981d7a5446e153829dbf9853d8061

Observation b23b7a7a-b96a-43e5-ac4f-1878e2593e46 · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T18:37:26.578426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:37:26.578426Z digest=sha256:e4742b169be60c2cc707408a916200f028afc50f9cda8328aed7bfb509f70671

Observation 3bbef34e-1c49-475e-ad9c-8ff67887f842 · outbound

This paper cites Neural architecture search: A survey,.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Neural architecture search: A survey,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:37:26.947671Z

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.

source=arxiv_source observed=2026-08-12T18:37:26.582055Z digest=sha256:8521288ba71b3408e20ca8148018d946433af6fab3d99308150a310247e9f4d7

Observation 6db557ac-13a4-4ce9-ac19-a421c92b6f49 · outbound

This paper cites Federated learning: Challenges, methods, and future directions,.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Federated learning: Challenges, methods, and future directions,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:37:26.936654Z

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.

source=arxiv_source observed=2026-08-12T18:37:26.585349Z digest=sha256:a04a3893973ef54704df8ecc0f5b20d29c21c565c3c13e61d61896350760f3fa

Observation 50797fac-b45c-4e03-959e-6a85bcda350e · outbound

This paper cites MobileBERT: a compact task-agnostic BERT for resource-limited devices,.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods MobileBERT: a compact task-agnostic BERT for resource-limited devices,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:37:26.925002Z

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.

source=arxiv_source observed=2026-08-12T18:37:26.589881Z digest=sha256:99afd76437cbb873a82920b94450845188e0cf2d6572c968e43fe1d2bcf55d16

Observation ed0458cc-f462-4833-9c04-cab822f3ffbf · outbound

This paper cites Apple's Neural Engine: 16-core architecture, delivering high performance for machine learning tasks,.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Apple's Neural Engine: 16-core architecture, delivering high performance for machine learning tasks,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:37:26.913433Z

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.

source=arxiv_source observed=2026-08-12T18:37:26.594545Z digest=sha256:b421be0046d90d69f55ca7e24dd6a19fb6870bc137363789d219d2a44a545d36

Observation 97ebc949-a764-4ae3-9ead-5aa76b8b643d · outbound

This paper cites A survey on the optimization of neural network accelerators for edge computing,.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods A survey on the optimization of neural network accelerators for edge computing,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:37:26.900698Z

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.

source=arxiv_source observed=2026-08-12T18:37:26.598780Z digest=sha256:d3a1552fa441496a3b3b3d3b3f8a513d94c79592b4433b61d98d95cd8f1b133f

Observation 05d1e019-67a5-48d4-a4cc-593f687cb0f7 · outbound

This paper cites Federated Learning with Non-IID Data.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Federated Learning with Non-IID Data

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T18:37:26.602471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:37:26.602471Z digest=sha256:840f2a9be49e85f66f51a33a724611ceae8c454f41dabf2d39a68d86db67fc99

Observation 31048785-2fa7-4378-aa67-9e4acda90314 · outbound

This paper cites On Self-Distilling Graph Neural Network.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods On Self-Distilling Graph Neural Network

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-12T18:37:26.607046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:37:26.607046Z digest=sha256:168ab2dace1f6a4e94d9d41ad4b8c4d6a5ee9aa7151e2f358b0a5fd334d93fa9

Observation 8b3dfa2d-32e1-46b2-a702-7babfb961d72 · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-12T18:37:26.611140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:37:26.611140Z digest=sha256:316a967c44615adeb74c95fe72e84263342cd7978903763fd8a587915a5ea7d0

Observation bd172b7d-558a-4692-9db3-7764f8a3b6f6 · outbound

This paper cites CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning.

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-12T18:37:26.615011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:37:26.615011Z digest=sha256:c9c90af5518edbb09fc5b18b31a0ab05375d1eaa08728287c0cc5804caefb387

Pith citing papers

No inbound Pith citation observations are available.