Paper Citation Record · LEDGER

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects

As of 23 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 2 inbound Pith citation observations for arXiv:2505.03303.

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

pith.paper-citation-record.v1
2505.03303 v5

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:59:30.459655Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:20:59.826611Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T17:28:44.128150Z

Reference resolution

26 of 26 outbound references displayed

verified exact0
verified fuzzy21
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7662cc45-ed02-4e41-b4a0-a8e3b18453db · outbound

This paper cites Deep learning,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Deep learning,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T23:59:30.335512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cac40c40-4c57-4058-9726-1f78f08a5c06 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Imagenet: A large-scale hierarchical image database,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.917379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 005df05f-fbcb-497a-a4cc-7b19d143e51c · outbound

This paper cites Learning both weights and connections for efficient neural networks,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Learning both weights and connections for efficient neural networks,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.898737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4c21d54a-a825-49d6-b47b-9b18505937e2 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T23:59:30.351123Z

Source-reported events for the cited work

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Observation 3545655f-7c5f-485a-b70b-db82175cdf3e · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Mobilenetv2: Inverted residuals and linear bottlenecks,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.880395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 009eb234-0d55-4001-9f34-f3a06da679b2 · outbound

This paper cites Searching for mobilenetv3,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Searching for mobilenetv3,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.862154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1b6baf1c-25e6-4179-b573-1357fd64836f · outbound

This paper cites SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T23:59:30.367785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e8afc5a-35ce-4b34-b5aa-5a5041e9e42c · outbound

This paper cites Efficientnetv2: Smaller models and faster training,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Efficientnetv2: Smaller models and faster training,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.838970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 047e9596-5f9b-4ebd-9aaa-12a879facf9d · outbound

This paper cites Deep residual learning for image recognition,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Deep residual learning for image recognition,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.822032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 15045054-42e2-4bfe-9db5-98e2cae240b1 · outbound

This paper cites Shufflenet v2: Practical guidelines for efficient cnn architecture design,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Shufflenet v2: Practical guidelines for efficient cnn architecture design,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.804348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2ce95985-d8c9-4652-9506-c2ee14fa33e2 · outbound

This paper cites Do better imagenet models transfer better?.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Do better imagenet models transfer better?

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.786193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0118a06f-e4cd-4462-a811-8aad135b6448 · outbound

This paper cites Regnet: Designing network design spaces,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Regnet: Designing network design spaces,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.767431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 90898625-73c2-4fe1-b1d3-a362476851d2 · outbound

This paper cites Learning multiple layers of features from tiny images,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Learning multiple layers of features from tiny images,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T23:59:30.397511Z

Source-reported events for the cited work

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Observation 8afc0576-061f-4eef-a96f-73cbbea68abb · outbound

This paper cites Mixup: Beyond empirical risk minimization,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Mixup: Beyond empirical risk minimization,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.739675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c327c2e7-914d-4bce-b518-7c112df7edf3 · outbound

This paper cites A survey on image data augmentation for deep learning,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects A survey on image data augmentation for deep learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.722890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 48b2f7e8-4d42-4d30-a60d-4983c7f817f8 · outbound

This paper cites Cutmix: Regularization strategy to train strong classifiers with localizable features,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Cutmix: Regularization strategy to train strong classifiers with localizable features,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.705094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c33aa027-96d9-4854-a09a-109fe0514e2f · outbound

This paper cites Efficient deep learning for edge computing platforms,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Efficient deep learning for edge computing platforms,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.687044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8640b267-8cbc-452f-947b-fcd4b18b8742 · outbound

This paper cites Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.668162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7cdd7144-432a-41aa-919f-4cb9b2777802 · outbound

This paper cites A comprehensive survey of deep learning-based lightweight object detection models for edge devices,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects A comprehensive survey of deep learning-based lightweight object detection models for edge devices,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.649639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 81bf0fd4-4ddb-419b-9c0d-bd5876110826 · outbound

This paper cites Evolution toward intelligent communications: Impact of deep learning applications on the future of 6g technology,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Evolution toward intelligent communications: Impact of deep learning applications on the future of 6g technology,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.633555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5acc1211-5ffb-4f89-8e07-6f127207d20d · outbound

This paper cites Image super- resolution using generative adversarial networks with efficientnetv2,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Image super- resolution using generative adversarial networks with efficientnetv2,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.615282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5b8bc819-2dba-4109-ab48-008ce892aa1e · outbound

This paper cites Pneumonia detection using deep convolutional neural net- works,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Pneumonia detection using deep convolutional neural net- works,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.597116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 287c8217-2d9e-410a-86ac-dd23573ce867 · outbound

This paper cites Shufflenet v2: Practical guidelines for efficient cnn architecture design,.

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T23:59:30.444802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cfa9b3a-649d-4ba1-b32d-ba812073f298 · outbound

This paper cites Randaugment: Practical automated data augmentation with a reduced search space,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Randaugment: Practical automated data augmentation with a reduced search space,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.568485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ee4fbed2-f3ed-4d8e-9458-1ae65ab6273c · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.550704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0c474336-ea2c-4656-909c-84ee0f88c5e9 · outbound

This paper cites A unified approach to interpreting model predictions,.

Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects A unified approach to interpreting model predictions,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:59:30.532652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation 38aca280-74e8-479b-9ac3-d8b8351dfb1e · inbound

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions cites this paper.

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects

Reference 152

Resolution: unresolved; no resolver link, observed 2026-08-05T16:20:59.826611Z

Source-reported events for the cited work

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Observation f66ecfcf-250e-4fd5-9d29-441b3ce6e9bf · inbound

Do Newer Lightweight CNNs Perform Better Under Resource Constraints? A Controlled Multigenerational Study of Architecture, Initialization, Training Budget, and Efficiency cites this paper.

Do Newer Lightweight CNNs Perform Better Under Resource Constraints? A Controlled Multigenerational Study of Architecture, Initialization, Training Budget, and Efficiency Comparative Analysis of Lightweight CNNs for Resource-Constrained Devices: Predictive Performance, Efficiency Trade-offs, and Initialization Effects

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-07-03T17:28:44.129484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.