Paper Citation Record · LEDGER

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device

As of 10 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2502.05800.

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

pith.paper-citation-record.v1
2502.05800 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:58:04.812467Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

27 of 27 outbound references displayed

verified exact0
verified fuzzy18
unresolved9
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 59f2a237-cb68-4b2d-9a11-6b2163b479ad · outbound

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

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T17:58:04.741398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02d8c1bb-691b-40af-9e26-bd22e4f25a0a · outbound

This paper cites Multi- stage vision transformer for batik classification,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Multi- stage vision transformer for batik classification,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:05.031828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 893f065f-bec7-434f-9727-8170cc21939e · outbound

This paper cites Swin transformer for pedestrian and occluded pedestrian detection,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Swin transformer for pedestrian and occluded pedestrian detection,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:05.023404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 44950125-f96b-4378-a066-0bc494b8c56a · outbound

This paper cites Metformer: A motion enhanced transformer for multiple object tracking,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Metformer: A motion enhanced transformer for multiple object tracking,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:05.014185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7cd0ea31-ccd1-4af8-b2b9-035e86b55364 · outbound

This paper cites Spik- ingvit: a multi-scale spiking vision transformer model for event-based object detection,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Spik- ingvit: a multi-scale spiking vision transformer model for event-based object detection,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:05.005810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e424e00b-a465-49e6-9670-1a6be41219a2 · outbound

This paper cites Inpainting diffusion synthetic and data augment with feature keypoints for tiny partial fingerprints,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Inpainting diffusion synthetic and data augment with feature keypoints for tiny partial fingerprints,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.996358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 43282867-5fe8-47b2-94ce-f28008cd6305 · outbound

This paper cites Fpga-based batik classification using quantization aware training of mobilenet and data- flow implementation,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Fpga-based batik classification using quantization aware training of mobilenet and data- flow implementation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.987979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c8fa5d7b-7fe6-49ab-957a-6935cc2713fb · outbound

This paper cites MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T17:58:04.763070Z

Source-reported events for the cited work

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Observation 40422421-87ef-4adb-bd36-4dac391f8c7e · outbound

This paper cites Cvt: Introducing convolutions to vision transformers,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Cvt: Introducing convolutions to vision transformers,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.979546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 779b7e31-0bf1-491f-abca-6041f982f8d2 · outbound

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

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Mobilenetv2: Inverted residuals and linear bottlenecks,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T17:58:04.768393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e998098-5081-49fc-8451-52e5270c983a · outbound

This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.966794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 89bc9b10-f41a-4a18-bc44-be5888c6bac9 · outbound

This paper cites Separable Self-attention for Mobile Vision Transformers.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Separable Self-attention for Mobile Vision Transformers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T17:58:04.772771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ad7cba3-fc11-41d0-ba66-9a268ce4dd23 · outbound

This paper cites Edgenext: efficiently amalgamated cnn- transformer architecture for mobile vision applications,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Edgenext: efficiently amalgamated cnn- transformer architecture for mobile vision applications,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.958514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 45607b23-9e98-4076-ade5-f0f04e6103f9 · outbound

This paper cites Fastvit: A fast hybrid vision transformer using structural reparameterization,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Fastvit: A fast hybrid vision transformer using structural reparameterization,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.949857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 651a5058-6dd5-47e2-9c60-42eab5284bae · outbound

This paper cites Rethinking vision transformers for mobilenet size and speed,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Rethinking vision transformers for mobilenet size and speed,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.941525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2d09db95-a630-421d-9765-c5fc124de584 · outbound

This paper cites Mobileone: An improved one millisecond mobile backbone,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Mobileone: An improved one millisecond mobile backbone,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.934011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 481e8bdf-a5aa-4cf4-9b1a-ff107e5911f0 · outbound

This paper cites Shvit: Single-head vision transformer with memory efficient macro design,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Shvit: Single-head vision transformer with memory efficient macro design,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.926600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 84d60219-f959-4ae8-9e52-1a3ccfc43970 · outbound

This paper cites Metaformer is actually what you need for vision,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Metaformer is actually what you need for vision,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.919035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6bc7049b-3b0b-48dd-bbca-f40d213174d2 · outbound

This paper cites Imagenet large scale visual recognition challenge,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Imagenet large scale visual recognition challenge,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T17:58:04.789639Z

Source-reported events for the cited work

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Observation 99ff4849-dd3e-45b3-b0b7-ac3a3e64d89b · outbound

This paper cites Training data-efficient image transformers & distillation through attention,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Training data-efficient image transformers & distillation through attention,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T17:58:04.792540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a60f83fd-5124-44a5-91e1-dd61261d6aaf · outbound

This paper cites Decoupled Weight Decay Regularization.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Decoupled Weight Decay Regularization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T17:58:04.795604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fece45c9-eec0-4789-9647-762611ce9455 · outbound

This paper cites Microsoft coco: Common objects in context,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Microsoft coco: Common objects in context,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T17:58:04.798731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e64271d-fd3b-43eb-b015-d5e72d487e34 · outbound

This paper cites Focal loss for dense object detection,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Focal loss for dense object detection,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.897883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4354da48-9042-41ab-9c3b-aa0c01f680ee · outbound

This paper cites Efficientvit: Memory efficient vision transformer with cascaded group attention,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Efficientvit: Memory efficient vision transformer with cascaded group attention,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.889689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 72950951-9fca-4b79-a371-d41afdd6b872 · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T17:58:04.806808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0c0c8e7-2e6f-4d46-86e6-a88dd0681219 · outbound

This paper cites Run, don’t walk: chasing higher flops for faster neural networks,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Run, don’t walk: chasing higher flops for faster neural networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.881205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 48a1eb33-7b5c-491f-9532-63207fd1351d · outbound

This paper cites Searching for mobilenetv3,.

MicroViT: A Vision Transformer with Low Complexity Self Attention for Edge Device Searching for mobilenetv3,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:58:04.872576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.