Paper Citation Record · LEDGER

ImageNet-21K Pretraining for the Masses

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 37 inbound Pith citation observations for arXiv:2104.10972.

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

pith.paper-citation-record.v1
2104.10972 v4

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 37 of 37 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:34:55.362129Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

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External citation measurements

4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 32d51985-98c8-4073-87a5-01aa653416f0 · inbound

LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment cites this paper.

LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment ImageNet-21K Pretraining for the Masses

Reference 208

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MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices cites this paper.

MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices ImageNet-21K Pretraining for the Masses

Reference 101

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UniGen: Enhanced Training & Test-Time Strategies for Unified Multimodal Understanding and Generation cites this paper.

UniGen: Enhanced Training & Test-Time Strategies for Unified Multimodal Understanding and Generation ImageNet-21K Pretraining for the Masses

Reference 55

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SNAP: A Benchmark for Testing the Effects of Capture Conditions on Fundamental Vision Tasks cites this paper.

SNAP: A Benchmark for Testing the Effects of Capture Conditions on Fundamental Vision Tasks ImageNet-21K Pretraining for the Masses

Reference 70

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PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation cites this paper.

PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation ImageNet-21K Pretraining for the Masses

Reference 50

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Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning cites this paper.

Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning ImageNet-21K Pretraining for the Masses

Reference 55

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Textile Analysis for Recycling Automation using Transfer Learning and Zero-Shot Foundation Models cites this paper.

Textile Analysis for Recycling Automation using Transfer Learning and Zero-Shot Foundation Models ImageNet-21K Pretraining for the Masses

Reference 24

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RollingQ: Reviving the Cooperation Dynamics in Multimodal Transformer cites this paper.

RollingQ: Reviving the Cooperation Dynamics in Multimodal Transformer ImageNet-21K Pretraining for the Masses

Reference 38

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Revisiting Audio-Visual Segmentation with Vision-Centric Transformer cites this paper.

Revisiting Audio-Visual Segmentation with Vision-Centric Transformer ImageNet-21K Pretraining for the Masses

Reference 32

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Opto-ViT: Architecting a Near-Sensor Region of Interest-Aware Vision Transformer Accelerator with Silicon Photonics cites this paper.

Opto-ViT: Architecting a Near-Sensor Region of Interest-Aware Vision Transformer Accelerator with Silicon Photonics ImageNet-21K Pretraining for the Masses

Reference 46

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Towards Continuous Home Cage Monitoring: An Evaluation of Tracking and Identification Strategies for Laboratory Mice cites this paper.

Towards Continuous Home Cage Monitoring: An Evaluation of Tracking and Identification Strategies for Laboratory Mice ImageNet-21K Pretraining for the Masses

Reference 24

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Smelly, dense, and spreaded: The Object Detection for Olfactory References (ODOR) dataset cites this paper.

Smelly, dense, and spreaded: The Object Detection for Olfactory References (ODOR) dataset ImageNet-21K Pretraining for the Masses

Reference 79

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ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation cites this paper.

ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation ImageNet-21K Pretraining for the Masses

Reference 33

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GVCCS: A Dataset for Contrail Identification and Tracking on Visible Whole Sky Camera Sequences cites this paper.

GVCCS: A Dataset for Contrail Identification and Tracking on Visible Whole Sky Camera Sequences ImageNet-21K Pretraining for the Masses

Reference 35

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Page image classification for content-specific data processing cites this paper.

Page image classification for content-specific data processing ImageNet-21K Pretraining for the Masses

Reference 16

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CascadeFormer: A Family of Two-stage Cascading Transformers for Skeleton-based Human Action Recognition cites this paper.

CascadeFormer: A Family of Two-stage Cascading Transformers for Skeleton-based Human Action Recognition ImageNet-21K Pretraining for the Masses

Reference 22

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Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization cites this paper.

Revisiting Deepfake Detection: Chronological Continual Learning and the Limits of Generalization ImageNet-21K Pretraining for the Masses

Reference 47

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H3Former: Hypergraph-based Semantic-Aware Aggregation via Hyperbolic Hierarchical Contrastive Loss for Fine-Grained Visual Classification cites this paper.

H3Former: Hypergraph-based Semantic-Aware Aggregation via Hyperbolic Hierarchical Contrastive Loss for Fine-Grained Visual Classification ImageNet-21K Pretraining for the Masses

Reference 41

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HandyLabel: Towards Post-Processing to Real-Time Annotation Using Skeleton Based Hand Gesture Recognition cites this paper.

HandyLabel: Towards Post-Processing to Real-Time Annotation Using Skeleton Based Hand Gesture Recognition ImageNet-21K Pretraining for the Masses

Reference 26

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MePo: Meta Post-Refinement for Rehearsal-Free General Continual Learning cites this paper.

MePo: Meta Post-Refinement for Rehearsal-Free General Continual Learning ImageNet-21K Pretraining for the Masses

Reference 5

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CanViT: Toward Active-Vision Foundation Models cites this paper.

CanViT: Toward Active-Vision Foundation Models ImageNet-21K Pretraining for the Masses

Reference 58

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StableTTA: Improving Vision Model Performance by Training-free Test-Time Adaptation Methods cites this paper.

StableTTA: Improving Vision Model Performance by Training-free Test-Time Adaptation Methods ImageNet-21K Pretraining for the Masses

Reference 27

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4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview cites this paper.

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview ImageNet-21K Pretraining for the Masses

Reference 45

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Contrastive Semantic Projection: Faithful Neuron Labeling with Contrastive Examples cites this paper.

Contrastive Semantic Projection: Faithful Neuron Labeling with Contrastive Examples ImageNet-21K Pretraining for the Masses

Reference 24

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Parameter-Efficient Adaptation of Pre-Trained Vision Foundation Models for Active and Passive Seismic Data Denoising cites this paper.

Parameter-Efficient Adaptation of Pre-Trained Vision Foundation Models for Active and Passive Seismic Data Denoising ImageNet-21K Pretraining for the Masses

Reference 46

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Birds of a Feather Flock Together: Background-Invariant Representations via Linear Structure in VLMs cites this paper.

Birds of a Feather Flock Together: Background-Invariant Representations via Linear Structure in VLMs ImageNet-21K Pretraining for the Masses

Reference 33

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Weierstrass Positional Encoding for Vision Transformers cites this paper.

Weierstrass Positional Encoding for Vision Transformers ImageNet-21K Pretraining for the Masses

Reference 32

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JetViT: Efficient High-Resolution Vision Transformer with Post-Training Attention Search cites this paper.

JetViT: Efficient High-Resolution Vision Transformer with Post-Training Attention Search ImageNet-21K Pretraining for the Masses

Reference 37

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Energy-Structured Low-Rank Adaptation for Continual Learning cites this paper.

Energy-Structured Low-Rank Adaptation for Continual Learning ImageNet-21K Pretraining for the Masses

Reference 5

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LV-OSD: Language-Vision-Complementary Open-Set Object Detection cites this paper.

LV-OSD: Language-Vision-Complementary Open-Set Object Detection ImageNet-21K Pretraining for the Masses

Reference 39

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VISReg: Variance-Invariance-Sketching Regularization for JEPA training cites this paper.

VISReg: Variance-Invariance-Sketching Regularization for JEPA training ImageNet-21K Pretraining for the Masses

Reference 8

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Page image classifier fine-tuned on century-spanning archives of scanned documents for further content-specific processing cites this paper.

Page image classifier fine-tuned on century-spanning archives of scanned documents for further content-specific processing ImageNet-21K Pretraining for the Masses

Reference 14

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ExDet: Open-Domain Open-Vocabulary Detection with Cross-modal Extrapolation and Rectification cites this paper.

ExDet: Open-Domain Open-Vocabulary Detection with Cross-modal Extrapolation and Rectification ImageNet-21K Pretraining for the Masses

Reference 36

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The Edge-on Galaxies in the DESI survey (EGIDE): sample building and photometry cites this paper.

The Edge-on Galaxies in the DESI survey (EGIDE): sample building and photometry ImageNet-21K Pretraining for the Masses

Reference 106

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The Edge-on Galaxies in the DESI survey (EGIDE): sample building and photometry cites this paper.

The Edge-on Galaxies in the DESI survey (EGIDE): sample building and photometry ImageNet-21K Pretraining for the Masses

Reference 106

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Identifying Latent Concepts and Structures for Generalized Category Discovery cites this paper.

Identifying Latent Concepts and Structures for Generalized Category Discovery ImageNet-21K Pretraining for the Masses

Reference 87

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Condensing Large-Scale Datasets Directly with Minimal Information Loss cites this paper.

Condensing Large-Scale Datasets Directly with Minimal Information Loss ImageNet-21K Pretraining for the Masses

Reference 28

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