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Paper Citation Record · LEDGER

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning

As of 11 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2505.21533.

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

pith.paper-citation-record.v1
2505.21533 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:38:39.840512Z

measured 40 of 40 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

40 of 40 outbound references displayed

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  • verified fuzzy30
  • unresolved9
  • parse uncertain0
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  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6ddd5380-c979-4200-bdac-b333e3f42a04 · outbound

This paper cites M., Rupprecht, C., and Vedaldi, A.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning M., Rupprecht, C., and Vedaldi, A

Reference 1

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Observation 17f497ab-7b3f-4b39-8435-40b118e93257 · outbound

This paper cites M., Rupprecht, C., and Vedaldi, A.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning M., Rupprecht, C., and Vedaldi, A

Reference 2

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Observation ac0640ec-6d10-4c95-ab86-25500cd5aa76 · outbound

This paper cites Self-supervised learning from images with a joint-embedding predictive architecture.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Self-supervised learning from images with a joint-embedding predictive architecture

Reference 3

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Observation 8b5918ff-d9dd-4041-8043-adc883715eaf · outbound

This paper cites BEiT: BERT Pre-Training of Image Transformers.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning BEiT: BERT Pre-Training of Image Transformers

Reference 4

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Source-reported events for the cited work

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Observation db564f22-2e62-4ffb-bc5d-3b4be0dec3a3 · outbound

This paper cites Deep clustering for unsupervised learning of visual features.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Deep clustering for unsupervised learning of visual features

Reference 5

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Source-reported events for the cited work

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Observation f859c74b-020a-41b8-a370-92fb77a13aee · outbound

This paper cites Unsupervised pre-training of image features on non-curated data.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Unsupervised pre-training of image features on non-curated data

Reference 6

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Observation 327a43b8-8e91-4dcf-8fb8-c4b16a72f7cd · outbound

This paper cites Unsupervised Learning of Visual Features by Contrasting Cluster Assignments.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Unsupervised Learning of Visual Features by Contrasting Cluster Assignments

Reference 7

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Source-reported events for the cited work

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Observation 3c969de7-c227-48ff-9040-75f207d91d03 · outbound

This paper cites Emerging Properties in Self-Supervised Vision Transformers.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Emerging Properties in Self-Supervised Vision Transformers

Reference 8

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Source-reported events for the cited work

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Observation fa575810-b2a9-4828-b5f1-f3b6e58b20ae · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning A simple framework for contrastive learning of visual representations

Reference 9

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Source-reported events for the cited work

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Observation 3a11d135-170d-422e-9acd-cba0a9f913d3 · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Unresolved cited work

Reference 10

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Observation 973e9e84-a3f7-46b8-a020-fbfe15825904 · outbound

This paper cites An Empirical Study of Training Self-Supervised Vision Transformers.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning An Empirical Study of Training Self-Supervised Vision Transformers

Reference 11

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Source-reported events for the cited work

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Observation fe472474-05e9-4747-a820-3ceb93235d30 · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Sinkhorn distances: Lightspeed computation of optimal transport

Reference 12

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Source-reported events for the cited work

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Observation 488c8973-8f46-43fa-96fc-f9be17b9d141 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 13

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Source-reported events for the cited work

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Observation 5ffa0e3d-cdb1-4312-a95b-f11622c94c23 · outbound

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

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 14

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Source-reported events for the cited work

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Observation 0c5c4085-bc5d-40d1-b538-8d9c95042ec8 · outbound

This paper cites With a little help from my friends: Nearest-neighbor contrastive learning of visual representations.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning With a little help from my friends: Nearest-neighbor contrastive learning of visual representations

Reference 15

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Source-reported events for the cited work

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Observation 8c0da395-be4c-4fcc-a506-be2488ad5434 · outbound

This paper cites Mask R-CNN.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Mask R-CNN

Reference 16

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Source-reported events for the cited work

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Observation defa306e-7f8f-4fd4-9c6e-9f4dbeb78b55 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Momentum contrast for unsupervised visual representation learning

Reference 17

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Observation a0c82a36-480f-494f-a75f-e3e5a43f4f56 · outbound

This paper cites 3d object representations for fine-grained categorization.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning 3d object representations for fine-grained categorization

Reference 18

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Source-reported events for the cited work

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Observation 9444befb-404a-4b6d-b0b2-59c9cbce969e · outbound

This paper cites and Hinton, G.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning and Hinton, G

Reference 19

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Source-reported events for the cited work

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Observation fd1615a9-6f1d-4427-ae9f-a29c4a130e6a · outbound

This paper cites Efficient Self-supervised Vision Transformers for Representation Learning.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Efficient Self-supervised Vision Transformers for Representation Learning

Reference 20

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Observation ba786c4c-19e7-4180-8b69-4f6caebd7f80 · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Unresolved cited work

Reference 21

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Observation 7cf6c00a-2517-47de-8e25-9dd0da727513 · outbound

This paper cites Swin Transformer: Hierarchical Vision Transformer using Shifted Windows.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Reference 22

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Observation 625cdb16-274e-4b37-ae27-346340271fa7 · outbound

This paper cites and Zisserman, A.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning and Zisserman, A

Reference 23

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Source-reported events for the cited work

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Observation 62df311a-f73d-4254-ba63-5b2d3c0c693c · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Representation Learning with Contrastive Predictive Coding

Reference 24

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Observation cd2ea5a8-f0ac-43e7-8a9e-8075cf09e1f1 · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Unresolved cited work

Reference 25

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Observation 86272030-4416-4cf3-9a4b-a8b92ece1514 · outbound

This paper cites Revisiting Oxford and Paris: Large-scale image retrieval benchmarking.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Revisiting Oxford and Paris: Large-scale image retrieval benchmarking

Reference 26

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Observation 26d49d48-dcc6-4073-91cb-00c57d1695c0 · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning S., and Souza, C

Reference 27

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Source-reported events for the cited work

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Observation 645c72e2-0a13-4fd7-b6c3-d423d5e8dfa5 · outbound

This paper cites Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures

Reference 28

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Observation 2a56657f-3a21-41ba-9d0a-17f573656b62 · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning and Ram\' rez Rivera, A

Reference 29

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Observation 6b044078-25bc-4935-801f-77c6d6473da9 · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Unresolved cited work

Reference 30

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Source-reported events for the cited work

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Observation 75fad922-3fe8-4340-8c8b-861d9debc6c8 · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Training data-efficient image transformers & distillation through attention

Reference 31

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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.

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Observation 927e958e-8f63-451d-89dc-1deea49c043e · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Scan: Learning to classify images without labels

Reference 32

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Source-reported events for the cited work

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Observation f7af91b1-ca27-4482-a9e3-86fcbb4cdb16 · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning The inaturalist species classification and detection dataset

Reference 33

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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.

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Observation 6a32a035-54bb-4240-b9e3-af13f6901a42 · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning and Isola, P

Reference 34

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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.

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Observation 1fa3ce03-31fe-404b-97d2-1c7074fd365b · outbound

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Self-Organizing Visual Prototypes for Non-Parametric Representation Learning X., and Lin, D

Reference 35

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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.

source=arxiv_source observed=2026-08-07T14:38:39.262669Z digest=sha256:a1c6b0eb3b1500b33e4ab56e496bc83e119dfae11810264da5b87f9bafed075e

Observation d9040e5e-c0e8-403b-872a-4193ab97d502 · outbound

This paper cites Noise or signal: The role of image backgrounds in object recognition.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Noise or signal: The role of image backgrounds in object recognition

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:41.174518Z

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.

source=arxiv_source observed=2026-08-07T14:38:39.362270Z digest=sha256:db4329079ce997b649f5da964eab1f42916250a22001a1714eb28aecffeb722e

Observation c87fc19d-2dd4-4bcd-90b9-1bab9a81d013 · outbound

This paper cites Unified Perceptual Parsing for Scene Understanding.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Unified Perceptual Parsing for Scene Understanding

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:40.972097Z

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.

source=arxiv_source observed=2026-08-07T14:38:39.479505Z digest=sha256:b80d32031792d8e04eb5881f4cd736fe449d6d9f97e22e8949341b8a599a864e

Observation 09e65d56-d93d-4073-966f-ed4be76f350b · outbound

This paper cites Scene Parsing through ADE20k Dataset.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Scene Parsing through ADE20k Dataset

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:40.744822Z

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.

source=arxiv_source observed=2026-08-07T14:38:39.590833Z digest=sha256:fd3eeef0925ec05c8d84d176fc8151dc3e764bafd4b7e909d6accfd18467b3a3

Observation e5435694-89be-463a-a9ca-23a34f1c3816 · outbound

This paper cites iBOT: Image BERT Pre-Training with Online Tokenizer.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning iBOT: Image BERT Pre-Training with Online Tokenizer

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:38:40.485098Z

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.

source=arxiv_source observed=2026-08-07T14:38:39.739558Z digest=sha256:fb2adfe5c4fd79535d334d9ba58dbc7f7ab875bfa99235c0c572c35c4a2d5c38

Observation 2143b06b-a8f6-4317-be76-273b72446f17 · outbound

This paper cites write newline.

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning write newline

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:38:39.840512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:38:39.840512Z digest=sha256:614e82e4dc52bfa855fb100ca38c55b11eaedc93e154135ccfdcf791169ca7e6

Pith citing papers

No inbound Pith citation observations are available.