Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T23:50:07.591495Z
Paper Citation Record · LEDGER
Cluster and Predict Latent Patches for Improved Masked Image Modeling
As of 8 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 4 inbound Pith citation observations for arXiv:2502.08769.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:13:57.887170Z
A source-named dated measurement, never combined with another source.
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Reference resolution
74 of 74 outbound references displayed
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External citation measurements
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Outbound references
Observation e64fd209-0933-4b59-ada4-cfaecb37f555 · outbound
This paper cites Mim-refiner: A contrastive learning boost from intermediate pre-trained representations, 2024.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Mim-refiner: A contrastive learning boost from intermediate pre-trained representations, 2024
Reference 1
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Observation affb467d-cb62-4c25-9828-79d172f73d03 · outbound
This paper cites Self-labelling via simultaneous clustering and representation learning.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Self-labelling via simultaneous clustering and representation learning
Reference 2
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Observation 0727c0ae-930c-4d4b-8c3b-c049fbf98300 · outbound
This paper cites Masked siamese networks for label-efficient learning.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Masked siamese networks for label-efficient learning
Reference 3
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Observation e6156ec4-db27-40f2-a81a-717c9211a1fe · outbound
This paper cites Self-supervised learning from images with a joint-embedding predictive architecture.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Self-supervised learning from images with a joint-embedding predictive architecture
Reference 4
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Observation 5275a5ba-00c8-487a-ad6b-f04b4fc69dda · outbound
This paper cites data2vec: A general framework for self-supervised learning in speech, vision and language.
Cluster and Predict Latent Patches for Improved Masked Image Modeling data2vec: A general framework for self-supervised learning in speech, vision and language
Reference 5
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Observation 4be6fc8f-9ab6-4d6c-af2d-65de12a83abd · outbound
This paper cites Efficient self-supervised learning with contextualized target representations for vision, speech and language.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Efficient self-supervised learning with contextualized target representations for vision, speech and language
Reference 6
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Observation c9be6d1e-fd5d-4b7c-86f6-150fce1ae03e · outbound
This paper cites Beit: Bert pre-training of image transformers.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Beit: Bert pre-training of image transformers
Reference 7
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Observation 49a4743c-bf3b-44cf-bc36-1afee2967373 · outbound
This paper cites Stochastic positional embeddings improve masked image modeling.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Stochastic positional embeddings improve masked image modeling
Reference 8
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Observation 63f55369-b7a8-4b83-af5a-1cf91ecba547 · outbound
This paper cites Objectnet: A large-scale bias-controlled dataset for pushing the limits of object recognition models.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Objectnet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
Reference 9
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Observation c137fadc-b63d-471f-8164-ca9e43bb34b4 · outbound
This paper cites V-jepa: Latent video prediction for visual representation learning, 2023.
Cluster and Predict Latent Patches for Improved Masked Image Modeling V-jepa: Latent video prediction for visual representation learning, 2023
Reference 10
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Observation ee0fbd76-015e-464d-b862-02753ebe7013 · outbound
This paper cites Are we done with ImageNet?.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Are we done with ImageNet?
Reference 11
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This paper cites Depth pro: Sharp monocular metric depth in less than a second, 2024.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Depth pro: Sharp monocular metric depth in less than a second, 2024
Reference 12
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Observation c5041c8f-00d8-43bf-a525-84b137b495c4 · outbound
This paper cites A limited memory algorithm for bound constrained optimization.
Cluster and Predict Latent Patches for Improved Masked Image Modeling A limited memory algorithm for bound constrained optimization
Reference 13
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Observation 1a74868c-f175-4173-abce-6b9bea721d3d · outbound
This paper cites Deep clustering for unsupervised learning of visual features.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Deep clustering for unsupervised learning of visual features
Reference 14
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Observation 46d778fb-81a4-446e-a4bd-2b18a3848f5c · outbound
This paper cites Unsupervised learning of visual features by contrasting cluster assignments.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Unsupervised learning of visual features by contrasting cluster assignments
Reference 15
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This paper cites Emerging properties in self-supervised vision transformers.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Emerging properties in self-supervised vision transformers
Reference 16
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Observation 4a756af9-0202-4c6d-b631-66b09d57b9a8 · outbound
This paper cites Generative pretraining from pixels.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Generative pretraining from pixels
Reference 17
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Observation 3bd9c4c6-87ed-4f13-8763-89941078d6ea · outbound
This paper cites Towards a general-purpose foundation model for computational pathology.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Towards a general-purpose foundation model for computational pathology
Reference 18
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This paper cites A simple framework for contrastive learning of visual representations.
Cluster and Predict Latent Patches for Improved Masked Image Modeling A simple framework for contrastive learning of visual representations
Reference 19
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Cluster and Predict Latent Patches for Improved Masked Image Modeling An empirical study of training self-supervised vision transformers
Reference 20
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Cluster and Predict Latent Patches for Improved Masked Image Modeling The cityscapes dataset for semantic urban scene understanding
Reference 21
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Vision transformers need registers
Reference 22
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This paper cites Endodino: A foundation model for gi endoscopy, 2025.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Endodino: A foundation model for gi endoscopy, 2025
Reference 23
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Cluster and Predict Latent Patches for Improved Masked Image Modeling BERT: pre-training of deep bidirectional transformers for language understanding
Reference 24
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Unsupervised visual representation learning by context prediction
Reference 25
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Cluster and Predict Latent Patches for Improved Masked Image Modeling An image is worth 16x16 words: Transformers for image recognition at scale
Reference 26
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Cluster and Predict Latent Patches for Improved Masked Image Modeling o kman, M rten Wadenb \
Reference 27
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Scalable pre-training of large autoregressive image models
Reference 28
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Cluster and Predict Latent Patches for Improved Masked Image Modeling The pascal visual object classes (voc) challenge
Reference 29
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Eva: Exploring the limits of masked visual representation learning at scale
Reference 30
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Eva-02: A visual representation for neon genesis
Reference 31
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Rethinking patch dependence for masked autoencoders, 2024
Reference 32
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Unsupervised representation learning by predicting image rotations
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Moca: Self-supervised representation learning by predicting masked online codebook assignments
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Momentum contrast for unsupervised visual representation learning
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Masked autoencoders are scalable vision learners
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Natural adversarial examples
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Contrastive masked autoencoders are stronger vision learners
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Unresolved cited work
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Adam: A method for stochastic optimization
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Cluster and Predict Latent Patches for Improved Masked Image Modeling A path towards autonomous machine intelligence, 2022
Reference 41
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Deepseek-v3 technical report, 2024
Reference 42
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Decoupled weight decay regularization, 2017
Reference 43
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Torchvision: Pytorch's computer vision library
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Self-supervised learning of pretext-invariant representations
Reference 45
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Advancing human-centric ai for robust x-ray analysis through holistic self-supervised learning, 2024
Reference 46
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Representation Learning with Contrastive Predictive Coding
Reference 47
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Dinov2: Learning robust visual features without supervision
Reference 48
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Context encoders: Feature learning by inpainting
Reference 49
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Improving language understanding by generative pre-training, 2018
Reference 50
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Zero-shot text-to-image generation
Reference 51
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Cluster and Predict Latent Patches for Improved Masked Image Modeling Machine learning in python: Main developments and technology trends in data science, machine learning, and artificial intelligence, 2020
Reference 52
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Observation 73c077ff-2cc1-4778-8624-a62da0966b56 · outbound
This paper cites Do imagenet classifiers generalize to imagenet? In ICML, 2019.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Do imagenet classifiers generalize to imagenet? In ICML, 2019
Reference 53
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f538355e-5b4a-41fc-9748-0f59f7a2cf3f · outbound
This paper cites Imagenet large scale visual recognition challenge.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Imagenet large scale visual recognition challenge
Reference 54
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 01a3fa6a-3f2d-4fdd-a4ab-218ace82b162 · outbound
This paper cites Sigma: Sinkhorn-guided masked video modeling.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Sigma: Sinkhorn-guided masked video modeling
Reference 55
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 03793c26-e018-4988-bf34-f66bc7bed3a7 · outbound
This paper cites Web-scale k-means clustering.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Web-scale k-means clustering
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:50:07.777248Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation cc0bbcb5-b204-4ab4-b0dc-be01084b5aff · outbound
This paper cites Concerning nonnegative matrices and doubly stochastic matrices.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Concerning nonnegative matrices and doubly stochastic matrices
Reference 57
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 71497537-1fb9-4982-bf87-53b1e49aa061 · outbound
This paper cites Roformer: Enhanced transformer with rotary position embedding.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Roformer: Enhanced transformer with rotary position embedding
Reference 58
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e2afff0e-51a7-42b1-b489-665f78593d31 · outbound
This paper cites T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data.
Cluster and Predict Latent Patches for Improved Masked Image Modeling T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data
Reference 59
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9332855d-31d5-4d2f-9a77-9ce603cd036a · outbound
This paper cites Very high resolution canopy height maps from rgb imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Very high resolution canopy height maps from rgb imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar
Reference 60
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 24166dd7-4065-4acc-9070-5850df9f9304 · outbound
This paper cites Dino-tracker: Taming dino for self-supervised point tracking in a single video.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Dino-tracker: Taming dino for self-supervised point tracking in a single video
Reference 61
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 1012bfcb-709a-490e-b18c-2b191e835b12 · outbound
This paper cites Benchmarking representation learning for natural world image collections.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Benchmarking representation learning for natural world image collections
Reference 62
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 09bf2426-bffb-4417-8b0a-9992e740c291 · outbound
This paper cites Attention is all you need.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Attention is all you need
Reference 63
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d190232-a474-4e33-985c-9f74b17f81a3 · outbound
This paper cites Vincent, H.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Vincent, H
Reference 64
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 03a388a6-3cf3-4d29-9a55-502e65642cdd · outbound
This paper cites A foundation model for clinical-grade computational pathology and rare cancers detection.
Cluster and Predict Latent Patches for Improved Masked Image Modeling A foundation model for clinical-grade computational pathology and rare cancers detection
Reference 65
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2a4280e0-4b36-4d95-8c11-69ac599d0947 · outbound
This paper cites Sun database: Large-scale scene recognition from abbey to zoo.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Sun database: Large-scale scene recognition from abbey to zoo
Reference 66
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 89dfc7d7-8d07-4983-95b7-ed952a786bd0 · outbound
This paper cites Simmim: A simple framework for masked image modeling.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Simmim: A simple framework for masked image modeling
Reference 67
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation bd409697-b5c0-4df1-96f7-38e7d60df78d · outbound
This paper cites A whole-slide foundation model for digital pathology from real-world data.
Cluster and Predict Latent Patches for Improved Masked Image Modeling A whole-slide foundation model for digital pathology from real-world data
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T23:50:07.685696Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 52981f07-77ca-421e-959a-06d2635c58a3 · outbound
This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Depth anything: Unleashing the power of large-scale unlabeled data
Reference 69
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46bc9068-cfc6-4076-80ae-32ce6c0ac2b6 · outbound
This paper cites Depth anything v2, 2024 b.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Depth anything v2, 2024 b
Reference 70
- Resolution
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- raw_fallback, observed 2026-08-07T23:50:07.671669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d3f037b7-e65d-4465-a4f3-fafd8849fa92 · outbound
This paper cites Colorful image colorization.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Colorful image colorization
Reference 71
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 323e94d1-8d9b-417f-ab22-6bc31226f118 · outbound
This paper cites Cae v2: Context autoencoder with clip target, 2022.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Cae v2: Context autoencoder with clip target, 2022
Reference 72
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 94ef0851-dcbc-4bd1-8101-143584786c9a · outbound
This paper cites Scene parsing through ade20k dataset.
Cluster and Predict Latent Patches for Improved Masked Image Modeling Scene parsing through ade20k dataset
Reference 73
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4c25e21-09f6-4514-808f-03cd2fcdca3b · outbound
This paper cites ibot: Image bert pre-training with online tokenizer.
Cluster and Predict Latent Patches for Improved Masked Image Modeling ibot: Image bert pre-training with online tokenizer
Reference 74
- Resolution
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- raw_fallback, observed 2026-08-07T23:50:07.643482Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Pith citing papers
Observation c4e2b4b3-0965-4f08-9eee-0052b9bee9ca · inbound
Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion cites this paper.
Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion Cluster and Predict Latent Patches for Improved Masked Image Modeling
Reference 21
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ca6159f-0d2c-44c2-a94a-b60543384547 · inbound
Text-Conditional JEPA for Learning Semantically Rich Visual Representations cites this paper.
Text-Conditional JEPA for Learning Semantically Rich Visual Representations Cluster and Predict Latent Patches for Improved Masked Image Modeling
Reference 6
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 63d6c140-fce3-4bb0-a322-f08060f9b25b · inbound
UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation cites this paper.
UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation Cluster and Predict Latent Patches for Improved Masked Image Modeling
Reference 64
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 544ba040-2d98-410e-945d-49933a15a2e2 · inbound
Separating Representation from Reconstruction Enables Scalable Text Encoders cites this paper.
Separating Representation from Reconstruction Enables Scalable Text Encoders Cluster and Predict Latent Patches for Improved Masked Image Modeling
Reference 8
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.