Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T18:37:26.615011Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T18:37:26.615011Z
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
46 of 46 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 3c48b571-25ad-4dfd-9284-437f1a589779 · outbound
Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods COVID-19 Image Data Collection
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Observation 1cd51994-5375-4984-9171-9b7bab31a939 · outbound
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
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Observation 8d7587e3-67ad-4505-bb44-f8e1a1a65c3f · outbound
Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Mong, Safwan S
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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Bejnordi, Arnaud A
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Observation a9dc601c-0f64-4124-b4ad-f6b80c1b2581 · outbound
Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Decoupled weight decay regularization, 2019
Reference 5
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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Lungren, and Andrew Y
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Observation a6e385f0-f9ef-4c0b-91e1-234767f6858e · outbound
Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Sam 2: Segment anything in images and videos, 2024
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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Sze-To, A
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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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Observation e7663e4f-9ef1-4a06-88bd-976a29f2f58b · outbound
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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Observation 11f31b0c-9be1-4fed-a10e-c22242dfb69a · outbound
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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Observation 2e0f99f6-ea03-408d-bc45-fc97833c668d · outbound
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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Observation 8ce3eea2-1dc3-4ae7-9e37-20156258b9ae · outbound
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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Observation 431dfcd3-9478-45ce-bc31-019d99aecb9b · outbound
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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Observation 83308b91-c8c4-4edf-bf43-6ed0ead24d9d · outbound
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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Observation fbc0ad83-2a91-4864-851f-f973a7a4f4f6 · outbound
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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Observation df96d156-fad2-47fe-bef9-3c1cafd4920f · outbound
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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Observation 6bec14df-54fc-45f1-a42a-f7e6e20884ae · outbound
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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Observation fc88cbbb-0040-452a-9d88-e7ef834866ae · outbound
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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Observation 8cbe983b-7ffb-4e16-b1f0-2ebfa83453a6 · outbound
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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Observation 8d8c0d30-ebe2-4481-9977-c4f7abfd6659 · outbound
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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Observation 54515365-f8dd-4cf8-b355-ff6bfbe44de5 · outbound
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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Observation 6faad24c-f447-4e21-8a93-03bc4ea04a1b · outbound
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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Observation 4bc61b0b-378a-49e6-ae59-00da44999603 · outbound
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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Observation 35cacd47-6c07-400c-9ae3-8e26d814df0d · outbound
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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Observation 9e05010d-91a9-408a-a848-8adde94e7f2d · outbound
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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Observation 5244b64b-0f29-411b-b591-0693d9ba81be · outbound
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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Observation 993827c7-7701-4a6a-9097-6d45e95bba0c · outbound
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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Observation 2ddf5715-d6f5-441a-8236-0f8701b956fc · outbound
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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Observation d2facf37-794d-487a-9080-21c36abba450 · outbound
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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Observation c4fe1b50-dbf5-4bc0-adbf-d07aba5cc1be · outbound
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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Observation 63721411-3607-4135-88c2-25ac99232187 · outbound
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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Observation 408abfee-30ab-4672-8aee-f8b06b9e074a · outbound
Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Block Pruning For Faster Transformers
Reference 34
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Observation 853374ce-c998-4041-a2fb-4b994947d890 · outbound
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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Observation 298ef81d-a97c-4f6a-989e-cad0851a8f6a · outbound
Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Overcoming catastrophic forgetting in neural networks,
Reference 36
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Observation b23b7a7a-b96a-43e5-ac4f-1878e2593e46 · outbound
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
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Observation 3bbef34e-1c49-475e-ad9c-8ff67887f842 · outbound
Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Neural architecture search: A survey,
Reference 38
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Observation 6db557ac-13a4-4ce9-ac19-a421c92b6f49 · outbound
Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Federated learning: Challenges, methods, and future directions,
Reference 39
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Observation 50797fac-b45c-4e03-959e-6a85bcda350e · outbound
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
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Observation ed0458cc-f462-4833-9c04-cab822f3ffbf · outbound
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
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Observation 97ebc949-a764-4ae3-9ead-5aa76b8b643d · outbound
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
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Observation 05d1e019-67a5-48d4-a4cc-593f687cb0f7 · outbound
Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Federated Learning with Non-IID Data
Reference 43
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Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods On Self-Distilling Graph Neural Network
Reference 44
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Observation 8b3dfa2d-32e1-46b2-a702-7babfb961d72 · outbound
Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Reference 45
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Observation bd172b7d-558a-4692-9db3-7764f8a3b6f6 · outbound
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
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No inbound Pith citation observations are available.