Paper Citation Record · LEDGER

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification

As of 7 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2505.23961.

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

pith.paper-citation-record.v1
2505.23961 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:40:43.630821Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

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

32 of 32 outbound references displayed

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verified fuzzy27
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 97c62830-3ba3-4b58-889b-1a4b5d6a54cb · outbound

This paper cites Global production of tomato.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Global production of tomato

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:49.762900Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 596ed396-a4e7-4542-8c65-3af00cb21b4d · outbound

This paper cites Less is more: Lighter and faster deep neural architecture for tomato leaf disease classification,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Less is more: Lighter and faster deep neural architecture for tomato leaf disease classification,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:49.607805Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 889d6c81-0ab1-4c20-b875-9c13083306a8 · outbound

This paper cites an unresolved cited work.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:40:49.452267Z

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Observation 5c40aa46-1a0f-4b1b-9874-898959a7afae · outbound

This paper cites Plant disease detection and classification by deep learning—a review,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Plant disease detection and classification by deep learning—a review,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:49.246170Z

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Observation a9da1acf-2f22-47c8-8814-a6c01f39c36a · outbound

This paper cites A critical analysis of deep learning applications in crop pest classification: Promising pathways and limitations,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification A critical analysis of deep learning applications in crop pest classification: Promising pathways and limitations,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:49.093773Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 99423161-85b1-456f-b2b5-c038f9a0f010 · outbound

This paper cites Vision transformer meets convolutional neural network for plant disease classification,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Vision transformer meets convolutional neural network for plant disease classification,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:48.875518Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e59b8d5a-d1a5-4b9c-ac4b-ee60fed99f75 · outbound

This paper cites Rethinking cooking state recognition with vision transformers,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Rethinking cooking state recognition with vision transformers,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:48.601589Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4f43835e-f581-49d5-ba93-a94094782051 · outbound

This paper cites Vision transformer for plant disease detection: Plantvit,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Vision transformer for plant disease detection: Plantvit,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:48.325905Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d2f0d4b3-9caf-40ee-9ffc-af9e2eec2d86 · outbound

This paper cites Exe-net: Explainable ensemble network for potato leaf disease classification,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Exe-net: Explainable ensemble network for potato leaf disease classification,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:48.045935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ded6dd15-a245-4e6b-be72-e87cb4b860c9 · outbound

This paper cites An efficient transfer learning-based approach for apple leaf disease classification,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification An efficient transfer learning-based approach for apple leaf disease classification,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:47.701712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 127eb89e-056e-4bf5-b3d5-611a234ba0eb · outbound

This paper cites Deep learning in agriculture: A survey,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Deep learning in agriculture: A survey,

Reference 11

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Source-reported events for the cited work

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Observation 4d2b05e4-d550-48cf-9218-3c0082169e89 · outbound

This paper cites Cotton leaf disease identification using transfer learning,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Cotton leaf disease identification using transfer learning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:47.450992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c277f593-ca13-4565-87a6-c9b01b5766f3 · outbound

This paper cites Automatic mango leaf disease detection using different transfer learning models,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Automatic mango leaf disease detection using different transfer learning models,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:47.178897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3761577c-54be-4025-be16-bbf983ae2390 · outbound

This paper cites A novel machine learning approach for fast and efficient detection of mango leaf diseases,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification A novel machine learning approach for fast and efficient detection of mango leaf diseases,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:46.966134Z

Source-reported events for the cited work

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Observation 1e7486ca-5dfe-4bfb-b9a9-404cd62b446e · outbound

This paper cites Mangoleafbd: A comprehensive image dataset to classify diseased and healthy mango leaves,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Mangoleafbd: A comprehensive image dataset to classify diseased and healthy mango leaves,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:46.781302Z

Source-reported events for the cited work

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Observation 7a46c5f8-c0ff-483a-b6cf-d8e43136ca5f · outbound

This paper cites Detect bangladeshi mango leaf diseases using lightweight convolutional neural network,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Detect bangladeshi mango leaf diseases using lightweight convolutional neural network,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:46.591043Z

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Observation 7885bda3-e8b9-4694-892a-65265f5f89ed · outbound

This paper cites Leafnet: A proficient convolutional neural network for detecting seven prominent mango leaf diseases,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Leafnet: A proficient convolutional neural network for detecting seven prominent mango leaf diseases,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:46.432629Z

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Observation 6a2eb24e-00be-4695-81f7-f605ab7e441c · outbound

This paper cites Mobilevit: Light-weight, general-purpose, and mobile-friendly vision transformer,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Mobilevit: Light-weight, general-purpose, and mobile-friendly vision transformer,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:46.241559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7c5d86a9-5910-4dbb-bb13-5139ff71bc74 · outbound

This paper cites Efficientvit: Multi-scale linear attention for high-resolution dense prediction,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Efficientvit: Multi-scale linear attention for high-resolution dense prediction,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:46.071616Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 53859423-9610-4a92-b1ef-b47edba32295 · outbound

This paper cites Tinyvit: Fast pretraining distillation for small vision transformers,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Tinyvit: Fast pretraining distillation for small vision transformers,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:45.889213Z

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Observation 55fc98b4-37ba-4519-a3ef-515383770aa5 · outbound

This paper cites Attention is all you need,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Attention is all you need,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:45.720711Z

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Observation 7861c63f-0cc4-4e94-8ad3-ae769a11b0bc · outbound

This paper cites Gaitgcn++: Improving gcn-based gait recognition with part-wise attention and dropgraph,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Gaitgcn++: Improving gcn-based gait recognition with part-wise attention and dropgraph,

Reference 22

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Observation a47123d8-6698-42f8-b3ea-df33db951f2d · outbound

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

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 23

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

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Mobilenetv2: Inverted residuals and linear bottlenecks,

Reference 24

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This paper cites Two decades of bengali handwritten digit recognition: A survey,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Two decades of bengali handwritten digit recognition: A survey,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:45.188043Z

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Observation e2a2be5a-65c3-4b54-a533-0203841c843c · outbound

This paper cites Fruit quality assessment with densely connected convolutional neural network,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Fruit quality assessment with densely connected convolutional neural network,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:44.987287Z

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Observation 5b5eb6a7-8124-475a-aa96-1d0729cc9920 · outbound

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

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Imagenet: A large-scale hierarchical image database,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:44.788329Z

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This paper cites Do vision transformers see like convolutional neural networks?,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Do vision transformers see like convolutional neural networks?,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:44.579510Z

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This paper cites Adam: A method for stochastic optimization,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Adam: A method for stochastic optimization,

Reference 29

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Observation 86bffc42-34b3-4687-a370-c4d30ae7fea6 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Imagenet classification with deep convolutional neural networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:44.346299Z

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Observation ed78944a-5d8e-4c9e-bbeb-4ad02c28f0a0 · outbound

This paper cites Densely connected convolutional networks,.

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Densely connected convolutional networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:44.174137Z

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Observation d3e3eec5-8ef2-43b5-b3a4-8ff2e1a23a4f · outbound

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

MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:40:43.954153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.