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Paper Citation Record · LEDGER

GUESS: Generative Uncertainty Ensemble for Self Supervision

As of 15 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2412.02896.

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

pith.paper-citation-record.v1
2412.02896 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

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measured 52 of 52 standing notices

One-hop event checks from named stored sources.

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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

52 of 52 outbound references displayed

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External citation measurements

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Outbound references

Observation badd97f0-b102-49d0-b759-221e75150d48 · outbound

This paper cites Self-supervised visual feature learning with deep neural networks: A survey,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Self-supervised visual feature learning with deep neural networks: A survey,

Reference 1

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Observation e5b44321-0cc0-4c76-b4ef-faced1967eb7 · outbound

This paper cites A unified visual information preservation framework for self-supervised pre-training in medical image analysis,.

GUESS: Generative Uncertainty Ensemble for Self Supervision A unified visual information preservation framework for self-supervised pre-training in medical image analysis,

Reference 2

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Observation 6e85d702-b73f-419b-aa14-ca2808033b4a · outbound

This paper cites Deep active ensemble sam- pling for image classification,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Deep active ensemble sam- pling for image classification,

Reference 3

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Observation e77402be-6de9-4436-85ef-4715e10225ea · outbound

This paper cites Deep Bayesian Active Learning, A Brief Survey on Recent Advances.

GUESS: Generative Uncertainty Ensemble for Self Supervision Deep Bayesian Active Learning, A Brief Survey on Recent Advances

Reference 4

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Observation 94ad223a-b2b0-4b5c-8dc1-07840026eedf · outbound

This paper cites A survey on deep semi-supervised learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision A survey on deep semi-supervised learning,

Reference 5

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Observation 411746d0-605f-4327-8ad9-efe7fb84298c · outbound

This paper cites Active uncertainty representation learning: Toward more label efficiency in deep learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Active uncertainty representation learning: Toward more label efficiency in deep learning,

Reference 6

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Observation 679304ea-ebc6-4c32-aa66-ac9b8ba0a0ec · outbound

This paper cites Barlow twins: Self-supervised learning via redundancy reduction,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Barlow twins: Self-supervised learning via redundancy reduction,

Reference 7

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Observation 54c881f6-c784-4fe7-b980-560d5c040309 · outbound

This paper cites Fussl: Fuzzy uncertain self supervised learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Fussl: Fuzzy uncertain self supervised learning,

Reference 8

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Observation 936f617d-1bc2-4e4b-a6c3-229ad9071418 · outbound

This paper cites More synergy, less redundancy: Exploiting joint mutual in- formation for self-supervised learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision More synergy, less redundancy: Exploiting joint mutual in- formation for self-supervised learning,

Reference 9

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Observation 883b1252-e2bf-4b12-9138-27367886b24e · outbound

This paper cites Learning where to learn in cross-view self-supervised learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Learning where to learn in cross-view self-supervised learning,

Reference 10

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Observation c1cfd659-a4de-40bc-ae31-37477e4e235e · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

GUESS: Generative Uncertainty Ensemble for Self Supervision Representation Learning with Contrastive Predictive Coding

Reference 11

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Observation d0ce5ed5-1701-418c-9198-cd0f16eece27 · outbound

This paper cites Contrastive multiview coding,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Contrastive multiview coding,

Reference 12

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Source-reported events for the cited work

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Observation 652e28dd-1290-4e1d-9d5e-51e6f6f33907 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Momentum contrast for unsupervised visual representation learning,

Reference 13

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Observation 5288372b-707c-4cc0-b17d-ac476c68d4e5 · outbound

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

GUESS: Generative Uncertainty Ensemble for Self Supervision A simple framework for contrastive learning of visual representations,

Reference 14

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Observation 388fb47c-dccc-4177-98c8-445e46819a6b · outbound

This paper cites Learning representations by maximizing mutual information across views,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Learning representations by maximizing mutual information across views,

Reference 15

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Observation 5b3f70c2-732b-4b22-86c8-eddb60d22002 · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Bootstrap your own latent-a new approach to self-supervised learning,

Reference 16

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Observation be9bd45d-8623-4c4e-a437-fc10145c4cc1 · outbound

This paper cites Exploring simple siamese representation learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Exploring simple siamese representation learning,

Reference 17

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Observation 195f545d-0e56-4fda-9719-4360e3142097 · outbound

This paper cites Understanding self-supervised learn- ing dynamics without contrastive pairs,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Understanding self-supervised learn- ing dynamics without contrastive pairs,

Reference 18

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Observation ce7f272b-3183-4c95-bd14-21ed0e52daa1 · outbound

This paper cites Whitening for self-supervised representation learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Whitening for self-supervised representation learning,

Reference 19

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Observation c8a36c39-26a5-4208-ae9a-7e4d1a27261f · outbound

This paper cites Dense contrastive learning for self-supervised visual pre-training,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Dense contrastive learning for self-supervised visual pre-training,

Reference 20

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Observation 802bb068-86be-4010-956b-9503f5bacfe2 · outbound

This paper cites Propagate yourself: Exploring pixel-level consistency for unsupervised visual representation learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Propagate yourself: Exploring pixel-level consistency for unsupervised visual representation learning,

Reference 21

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Observation a8569b9b-0395-4bdf-ad7f-a0bd9b721906 · outbound

This paper cites Spatially consistent representation learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Spatially consistent representation learning,

Reference 22

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Observation a81e58a3-693d-4ee1-912b-5ebadb85896a · outbound

This paper cites Region similarity representation learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Region similarity representation learning,

Reference 23

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Observation 62c47a3e-a1f6-444b-83ed-9a4488a4e649 · outbound

This paper cites Self-supervised models are continual learners,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Self-supervised models are continual learners,

Reference 24

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Observation 8fa30b1d-8fa8-43e5-bc99-501caa931469 · outbound

This paper cites Lex fridman podcast, (MIT AI podcast). episode # 258.

GUESS: Generative Uncertainty Ensemble for Self Supervision Lex fridman podcast, (MIT AI podcast). episode # 258

Reference 25

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Observation 75371d40-8841-47d0-b74f-f0dd2387209e · outbound

This paper cites Using self- supervised learning can improve model robustness and uncertainty,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Using self- supervised learning can improve model robustness and uncertainty,

Reference 26

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Observation eb230b0b-2382-4c28-b2ad-f16700e1754a · outbound

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GUESS: Generative Uncertainty Ensemble for Self Supervision On the uncertainty of self-supervised monocular depth estimation,

Reference 27

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This paper cites Exploiting unlabeled data in cnns by self-supervised learning to rank,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Exploiting unlabeled data in cnns by self-supervised learning to rank,

Reference 28

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GUESS: Generative Uncertainty Ensemble for Self Supervision Self-supervised low-light image enhancement using discrepant untrained network priors,

Reference 29

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GUESS: Generative Uncertainty Ensemble for Self Supervision Self-supervised learning by estimating twin class distribution,

Reference 30

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Observation 19144bf1-632d-486a-a497-44fb9081016d · outbound

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GUESS: Generative Uncertainty Ensemble for Self Supervision Adversarial Feature Learning

Reference 31

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GUESS: Generative Uncertainty Ensemble for Self Supervision Unsupervised learning of visual features by contrasting cluster assign- ments,

Reference 32

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

GUESS: Generative Uncertainty Ensemble for Self Supervision Deep clustering for unsupervised learning of visual features,

Reference 33

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Observation c86528c2-0a83-4bcd-bd60-2cded50bd9ad · outbound

This paper cites Emerging properties in self-supervised vision transformers,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Emerging properties in self-supervised vision transformers,

Reference 34

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Observation 75539503-6a3d-43b6-b563-dd095d31dbc0 · outbound

This paper cites Improved deep metric learning with multi-class n-pair loss objective,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Improved deep metric learning with multi-class n-pair loss objective,

Reference 35

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Observation 4629ef4a-705b-43f3-b600-705ca12a42c9 · outbound

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GUESS: Generative Uncertainty Ensemble for Self Supervision Unsupervised learning of visual representations using videos,

Reference 36

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Observation 0d746e29-6727-46c9-aca2-ae80780199d0 · outbound

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GUESS: Generative Uncertainty Ensemble for Self Supervision Learning multiple layers of features from tiny images,

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:04:51.350792Z digest=sha256:1a7536127cf29d26cab939d2265632b61f9dfcf1164eff70755f8b0a176ef5cd

Observation 0c2d159b-5807-482a-bc64-ef60340fdec6 · outbound

This paper cites Tiny imagenet visual recognition challenge,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Tiny imagenet visual recognition challenge,

Reference 38

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no resolver link, observed 2026-08-11T23:04:51.359379Z

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source=pdf_text observed=2026-08-11T23:04:51.359379Z digest=sha256:db29f4aad483d30af8b6728b26fdfa245fb47f6384b5f13a24379ac0457c49f7

Observation 0f82ea12-c1ea-4677-9020-dac516379172 · outbound

This paper cites Deep residual learning for image recognition,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Deep residual learning for image recognition,

Reference 39

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unresolved
no resolver link, observed 2026-08-11T23:04:51.368639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:04:51.368639Z digest=sha256:a7528ec421c237fb429575c0cfa117c205826052c1d08f3fb3d9d1a95fce4101

Observation d3a410dc-328b-486d-aaf7-9cffd703639e · outbound

This paper cites Adam: A Method for Stochastic Optimization.

GUESS: Generative Uncertainty Ensemble for Self Supervision Adam: A Method for Stochastic Optimization

Reference 40

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no resolver link, observed 2026-08-11T23:04:51.377227Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T23:04:51.377227Z digest=sha256:fbfeda10981d60d15b4a9094237cc0ca261f349f2d57deb9cbaf2783215b082e

Observation bb012e8d-725c-4ea4-b9ef-146c7fc45b69 · outbound

This paper cites solo-learn: A library of self-supervised methods for visual representation learning.

GUESS: Generative Uncertainty Ensemble for Self Supervision solo-learn: A library of self-supervised methods for visual representation learning

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-11T23:04:52.213604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T23:04:51.385571Z digest=sha256:535a3c630729e5cc8a41257100e0c3717d7845b08e4d4caf6c8a8ea8fbad96e1

Observation 78c5ba0e-315b-453a-b3ad-5372b6118651 · outbound

This paper cites Directional self-supervised learning for heavy image augmentations,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Directional self-supervised learning for heavy image augmentations,

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-11T23:04:52.188514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T23:04:51.397576Z digest=sha256:e56be6447e54b35fdd569c967006f57f2f4f9f37ce6fb153b45232f512106559

Observation ba24f043-7887-466b-9820-74c3e17e6844 · outbound

This paper cites Shuffle and learn: unsupervised learning using temporal order verification,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Shuffle and learn: unsupervised learning using temporal order verification,

Reference 43

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verified fuzzy
raw_fallback, observed 2026-08-11T23:04:52.136912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T23:04:51.414326Z digest=sha256:b9201b2e372a40aef2f27c397bdc1eef05472d78889c4fba3dadb9b404838337

Observation 2a25f503-29b5-43b2-b320-46e3326e913c · outbound

This paper cites Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods.

GUESS: Generative Uncertainty Ensemble for Self Supervision Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods

Reference 44

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no resolver link, observed 2026-08-11T23:04:51.422124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:04:51.422124Z digest=sha256:8550bcf4f0ed50287e888178ffd1a3a9c90d2cf957a0b5fd89032d3799011579

Observation 11b72890-958c-434a-adc2-0eb2c678c2cb · outbound

This paper cites Uncertainty-aware self-supervised learning of spatial perception tasks,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Uncertainty-aware self-supervised learning of spatial perception tasks,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:04:52.093968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T23:04:51.433737Z digest=sha256:1b2ec5109777a4cf68f472c7413b7608fe8e2424c9cef7c46d4c8673a1fdd4db

Observation 5653f9e9-4fb1-41ee-947d-02f62dbfd521 · outbound

This paper cites Credal self-supervised learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Credal self-supervised learning,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:04:52.054693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T23:04:51.442075Z digest=sha256:6619542f26634eeb55bcf455c30d0e9f92cef8ac3d492f5c92514db73646dea1

Observation d8aa7ddb-5f55-41d4-8721-7c4cf4d44fe0 · outbound

This paper cites Cliquecnn: Deep unsupervised exemplar learning,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Cliquecnn: Deep unsupervised exemplar learning,

Reference 47

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verified fuzzy
raw_fallback, observed 2026-08-11T23:04:52.029467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T23:04:51.449933Z digest=sha256:eccd2d995b3622063f5d192daaabc2613a8c2b9a5559391b35ace92e826162f5

Observation 8adf3a2f-701a-4a73-9b60-afc113050696 · outbound

This paper cites Invariant information clustering for unsupervised image classification and segmentation,.

GUESS: Generative Uncertainty Ensemble for Self Supervision Invariant information clustering for unsupervised image classification and segmentation,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:04:52.004310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T23:04:51.463666Z digest=sha256:a9197dc271e8c532210504f3ec2c768337df0d2837f60bf7a4b374f5f902c947

Observation 0d904a08-3f5f-489c-9228-456e3b67c771 · outbound

This paper cites The information bottleneck method.

GUESS: Generative Uncertainty Ensemble for Self Supervision The information bottleneck method

Reference 49

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unresolved
no resolver link, observed 2026-08-11T23:04:51.475199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:04:51.475199Z digest=sha256:39533a8c7a6d02b8290ff3161260fae82c91b0cd096d6a70ad26b344914daead

Observation 5a8973c2-fa16-4b77-a70c-6982b2cb9f13 · outbound

This paper cites an unresolved cited work.

GUESS: Generative Uncertainty Ensemble for Self Supervision Unresolved cited work

Reference 50

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raw_fallback, observed 2026-08-11T23:04:51.981207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T23:04:51.488484Z digest=sha256:aaf481835605e1fd6c88afc5d34f1d2553543177dc2599e3bcd99e928018e3b5

Observation fe977180-bde4-418d-825c-e85e90b332ca · outbound

This paper cites an unresolved cited work.

GUESS: Generative Uncertainty Ensemble for Self Supervision Unresolved cited work

Reference 51

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raw_fallback, observed 2026-08-11T23:04:51.915085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T23:04:51.501724Z digest=sha256:a19c28a881dd2a877742c83de10e033854c21e959d9fc008cfc16c504c7a00a3

Observation 7a59caf7-1c7f-405a-9928-51ea5afdbfd4 · outbound

This paper cites this work proposes the use of credal sets to model uncertainty in pseudo-labels and hence reduce calibration errors in SSL approach.

GUESS: Generative Uncertainty Ensemble for Self Supervision this work proposes the use of credal sets to model uncertainty in pseudo-labels and hence reduce calibration errors in SSL approach

Reference 52

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verified fuzzy
raw_fallback, observed 2026-08-11T23:04:51.878993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T23:04:51.508348Z digest=sha256:c82fd24d0baa1b903cbb0dcf062c0574e31d45c6c0435e3f6d00c3112c8c628d

Pith citing papers

No inbound Pith citation observations are available.