Paper Citation Record · LEDGER

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 31 inbound Pith citation observations for arXiv:2106.10270.

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

pith.paper-citation-record.v1
2106.10270 v2

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measured 0 of 0 reference resolution

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measured 31 of 31 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 31 of 31 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:03:50.087516Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T18:15:59.170440Z

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Outbound references

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Pith citing papers

Observation c20ce74c-047f-410c-ac72-52b7bcc383ed · inbound

Sigmoid Loss for Language Image Pre-Training cites this paper.

Sigmoid Loss for Language Image Pre-Training How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-16T13:05:36.491069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 88d9375c-4005-4576-9c64-077b5c5fa2bc · inbound

Demystifying CLIP Data cites this paper.

Demystifying CLIP Data How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 80

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T09:20:20.323505Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1a7378d4-cace-4508-b514-cf3741ec5691 · inbound

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 185

Resolution: verified exact; arxiv_id, observed 2026-05-13T11:32:36.926712Z

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Observation 0a682dcd-0704-4295-8db7-3ac96b14c373 · inbound

$\pi_0$: A Vision-Language-Action Flow Model for General Robot Control cites this paper.

$\pi_0$: A Vision-Language-Action Flow Model for General Robot Control How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:38:24.532658Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2ff296f9-cc39-425d-85f6-cb943fced636 · inbound

DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations cites this paper.

DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-08T17:03:50.087516Z

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Observation 69e3555e-2820-42fc-8470-3b0b8cea1dab · inbound

TEMSET-24K: Densely Annotated Dataset for Indexing Multipart Endoscopic Videos using Surgical Timeline Segmentation cites this paper.

TEMSET-24K: Densely Annotated Dataset for Indexing Multipart Endoscopic Videos using Surgical Timeline Segmentation How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-08T14:37:59.632356Z

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Observation 255794bd-9d13-46bb-a48b-df6496b4b83c · inbound

Scaling Pre-training to One Hundred Billion Data for Vision Language Models cites this paper.

Scaling Pre-training to One Hundred Billion Data for Vision Language Models How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-08T12:12:30.787739Z

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Observation 9bc80515-111b-4fcf-8c17-1f8e21331cc1 · inbound

EMRA-proxy: Enhancing Multi-Class Region Semantic Segmentation in Remote Sensing Images with Attention Proxy cites this paper.

EMRA-proxy: Enhancing Multi-Class Region Semantic Segmentation in Remote Sensing Images with Attention Proxy How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T14:46:53.729509Z

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Observation 9fc44e78-5762-44f8-b03f-022e60c60f95 · inbound

TDVE-Assessor: Benchmarking and Evaluating the Quality of Text-Driven Video Editing with LMMs cites this paper.

TDVE-Assessor: Benchmarking and Evaluating the Quality of Text-Driven Video Editing with LMMs How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:47.047930Z

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Observation 764911ee-d831-4bb5-84c0-49aa58cfe182 · inbound

Leaner Transformers: More Heads, Less Depth cites this paper.

Leaner Transformers: More Heads, Less Depth How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T13:53:12.281412Z

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Observation 42585f21-2d84-489f-8b2a-e98b3c9bf0e0 · inbound

Moment Alignment: Unifying Gradient and Hessian Matching for Domain Generalization cites this paper.

Moment Alignment: Unifying Gradient and Hessian Matching for Domain Generalization How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T05:48:35.044872Z

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Observation 96bd96aa-b993-4134-9747-392bb262feb0 · inbound

Hidden in plain sight: VLMs overlook their visual representations cites this paper.

Hidden in plain sight: VLMs overlook their visual representations How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T05:25:31.940685Z

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Observation a7c6cb3a-4163-4dd1-afa1-20b9344c294f · inbound

InceptionMamba: An Efficient Hybrid Network with Large Band Convolution and Bottleneck Mamba cites this paper.

InceptionMamba: An Efficient Hybrid Network with Large Band Convolution and Bottleneck Mamba How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T05:07:14.444800Z

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Observation 3534d411-7f0c-4e82-8175-a40d15f136fb · inbound

ReStNet: A Reusable & Stitchable Network for Dynamic Adaptation on IoT Devices cites this paper.

ReStNet: A Reusable & Stitchable Network for Dynamic Adaptation on IoT Devices How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T05:44:09.801949Z

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Observation f3e75e37-b0af-4a03-8caf-d19a2825939c · inbound

DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding cites this paper.

DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T04:39:06.578252Z

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Observation 7c5922de-eae6-47b2-9b43-a83d6eb5ce41 · inbound

Pose Matters: Evaluating Vision Transformers and CNNs for Human Action Recognition on Small COCO Subsets cites this paper.

Pose Matters: Evaluating Vision Transformers and CNNs for Human Action Recognition on Small COCO Subsets How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T04:08:07.020403Z

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Observation 6b183a73-cc2c-4838-b1c5-c9976c695e2e · inbound

Underwater Monocular Metric Depth Estimation: Real-World Benchmarks and Synthetic Fine-Tuning with Vision Foundation Models cites this paper.

Underwater Monocular Metric Depth Estimation: Real-World Benchmarks and Synthetic Fine-Tuning with Vision Foundation Models How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T20:40:38.631360Z

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Observation a2560c90-33d3-4495-af18-358e1fb372a8 · inbound

Elastic ViTs from Pretrained Models without Retraining cites this paper.

Elastic ViTs from Pretrained Models without Retraining How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-04T09:03:09.342772Z

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Observation 272e2d83-974f-48ea-9120-5bf5c4981d82 · inbound

CoMViT: An Efficient Vision Backbone for Supervised Classification in Medical Imaging cites this paper.

CoMViT: An Efficient Vision Backbone for Supervised Classification in Medical Imaging How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T07:01:12.434996Z

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Observation f6043aef-f7c3-442b-9bf2-838d20253c18 · inbound

Towards Cellular-Scale Interpretability in Pathology Foundation Models for Biomarker Assessment cites this paper.

Towards Cellular-Scale Interpretability in Pathology Foundation Models for Biomarker Assessment How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T23:34:16.095023Z

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Observation f42dac14-2c5d-4b95-924e-1dc28f5ab6fc · inbound

Causal Attribution via Activation Patching cites this paper.

Causal Attribution via Activation Patching How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-21T11:10:02.082743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 376ee791-ad4f-4850-a5d1-1d93161eae35 · inbound

Human-like Object Grouping in Self-supervised Vision Transformers cites this paper.

Human-like Object Grouping in Self-supervised Vision Transformers How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-14T21:34:48.709465Z

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Observation a1b08e9a-7280-4fcb-9bf2-3e635174cd1d · inbound

Decision-Aware Attention Propagation for Vision Transformer Explainability cites this paper.

Decision-Aware Attention Propagation for Vision Transformer Explainability How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:01:01.755658Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b3c06afe-72a1-4860-af0a-567a789be8ec · inbound

Enjoy Your Layer Normalization with the Computational Efficiency of RMSNorm cites this paper.

Enjoy Your Layer Normalization with the Computational Efficiency of RMSNorm How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 57

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T02:33:32.625105Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7494ba04-06cb-448f-aa2a-656cd19c5252 · inbound

ASAP: Attention Sink Anchored Pruning cites this paper.

ASAP: Attention Sink Anchored Pruning How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-22T08:14:45.564776Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ae73bce2-3402-4ca3-b4fe-61ef2d1c7484 · inbound

Weierstrass Positional Encoding for Vision Transformers cites this paper.

Weierstrass Positional Encoding for Vision Transformers How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:50:23.743705Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 20056288-d1b1-4b65-933b-1b176bd3358e · inbound

Large Language Model Teaches Visual Students: Cross-Modality Transfer of Fine-Grained Conceptual Knowledge cites this paper.

Large Language Model Teaches Visual Students: Cross-Modality Transfer of Fine-Grained Conceptual Knowledge How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 63

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T18:15:59.172041Z

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Observation ebba460c-3cad-45ec-bfdd-c603b8daea9e · inbound

Screening Is Effective for Visual Recognition cites this paper.

Screening Is Effective for Visual Recognition How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T03:08:45.376016Z

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Observation cbcb636e-fb69-4db7-89e7-e96e75eb7dac · inbound

Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention cites this paper.

Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-01T13:33:15.789562Z

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Observation f1edc681-1762-4852-a8af-99802565b854 · inbound

Color Fundus Photography Analysis: Co-evolution of Data, Preprocessing, and Modeling toward Multimodal AI cites this paper.

Color Fundus Photography Analysis: Co-evolution of Data, Preprocessing, and Modeling toward Multimodal AI How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 186

Resolution: unresolved; no resolver link, observed 2026-07-31T23:27:36.860612Z

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Observation 8a185ae9-54d4-4b74-bfab-00f1a50c0bd0 · inbound

Representation Trajectories Matters: Complementary Evidence for OOD Detection and Image Classification cites this paper.

Representation Trajectories Matters: Complementary Evidence for OOD Detection and Image Classification How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-01T13:20:38.168263Z

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Unavailable: canonical work link unavailable.