Paper Citation Record · LEDGER

Generalized Category Discovery via Token Manifold Capacity Learning

As of 13 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 2 inbound Pith citation observations for arXiv:2505.14044.

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

pith.paper-citation-record.v1
2505.14044 v1

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:43:19.112811Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T22:18:36.329949Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T14:47:03.352709Z

Reference resolution

65 of 65 outbound references displayed

verified exact1
verified fuzzy42
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External citation measurements

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Outbound references

Observation ed691ab7-24d6-474f-b8dc-662f6c7c0f1c · outbound

This paper cites VICReg: Variance-invariance-covariance regularization for self-supervised learning.

Generalized Category Discovery via Token Manifold Capacity Learning VICReg: Variance-invariance-covariance regularization for self-supervised learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:33.432758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ebf7cd74-64de-49a9-bf87-488b04294de9 · outbound

This paper cites V on neumann entropy from unitarity.Physical review letters, 122(21):210402, 2019.

Generalized Category Discovery via Token Manifold Capacity Learning V on neumann entropy from unitarity.Physical review letters, 122(21):210402, 2019

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:33.221758Z

Source-reported events for the cited work

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Observation 80ad3b48-c0ba-4102-bd03-33f577f40986 · outbound

This paper cites Open-world semi-supervised learning.

Generalized Category Discovery via Token Manifold Capacity Learning Open-world semi-supervised learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:33.003422Z

Source-reported events for the cited work

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Observation bb47efd4-3402-4586-8e73-ba3a8340cc60 · outbound

This paper cites Unsu- pervised learning of visual features by contrasting cluster assignments.Advances in neural information processing systems, 33:9912–9924, 2020.

Generalized Category Discovery via Token Manifold Capacity Learning Unsu- pervised learning of visual features by contrasting cluster assignments.Advances in neural information processing systems, 33:9912–9924, 2020

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:32.722471Z

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Observation 5fbf9ddd-6bb6-4f10-83bc-9dc0f418a0f2 · outbound

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

Generalized Category Discovery via Token Manifold Capacity Learning Emerging properties in self-supervised vision transformers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:12.572883Z

Source-reported events for the cited work

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Observation e79e6853-a3de-4d60-b0a2-318341f42b03 · outbound

This paper cites Towards mitigating dimensional collapse of representations in collaborative filtering.

Generalized Category Discovery via Token Manifold Capacity Learning Towards mitigating dimensional collapse of representations in collaborative filtering

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:32.492231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cf78fe11-5134-4d33-bfdc-666ffb8f4dea · outbound

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

Generalized Category Discovery via Token Manifold Capacity Learning A simple framework for contrastive learning of visual representations

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:12.772682Z

Source-reported events for the cited work

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Observation fd37b850-9c32-49e4-805f-e7e2452e259d · outbound

This paper cites Parametric infor- mation maximization for generalized category discovery.

Generalized Category Discovery via Token Manifold Capacity Learning Parametric infor- mation maximization for generalized category discovery

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:32.291913Z

Source-reported events for the cited work

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Observation 2d4ed84e-e693-4a61-b58c-577a44572fe9 · outbound

This paper cites Utilizing class information for deep network representation shaping.

Generalized Category Discovery via Token Manifold Capacity Learning Utilizing class information for deep network representation shaping

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:32.057379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7a21236a-9874-4eca-9cea-efa10d8c9aaa · outbound

This paper cites Contrastive mean-shift learning for generalized category discovery.

Generalized Category Discovery via Token Manifold Capacity Learning Contrastive mean-shift learning for generalized category discovery

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:31.872444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b16471f8-555b-48be-a518-f6e198caab3d · outbound

This paper cites Reducing Overfitting in Deep Networks by Decorrelating Representations.

Generalized Category Discovery via Token Manifold Capacity Learning Reducing Overfitting in Deep Networks by Decorrelating Representations

Reference 11

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Source-reported events for the cited work

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Observation 620ab6bb-c47f-4125-aa00-dfb7cc13c85b · outbound

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

Generalized Category Discovery via Token Manifold Capacity Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:13.144856Z

Source-reported events for the cited work

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Observation d1dd5d8b-dd78-4e2b-b0a4-d71dc2a3daf4 · outbound

This paper cites Derivations for linear algebra and optimization.Berkeley, California, 3(1):2325–5870, 2007.

Generalized Category Discovery via Token Manifold Capacity Learning Derivations for linear algebra and optimization.Berkeley, California, 3(1):2325–5870, 2007

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:31.709400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3c800db9-39fe-46ed-b96d-4690bcd7d95d · outbound

This paper cites A unified objective for novel class discovery.

Generalized Category Discovery via Token Manifold Capacity Learning A unified objective for novel class discovery

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:31.518462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e201af7b-d1a2-4e64-a1b7-647f13a2e2d0 · outbound

This paper cites The role of entropy and reconstruction in multi-view self-supervised learning.

Generalized Category Discovery via Token Manifold Capacity Learning The role of entropy and reconstruction in multi-view self-supervised learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:31.318199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e4c9c93a-9654-49fc-b6d6-88a814bd1f9d · outbound

This paper cites Wichmann, and Wieland Brendel.

Generalized Category Discovery via Token Manifold Capacity Learning Wichmann, and Wieland Brendel

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:31.077266Z

Source-reported events for the cited work

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Observation d53c35b7-887c-4095-8c85-ed647c1b3a93 · outbound

This paper cites Recent advances in open set recognition: A survey.IEEE transactions on pattern analysis and machine intelligence, 43(10):3614–3631, 2020.

Generalized Category Discovery via Token Manifold Capacity Learning Recent advances in open set recognition: A survey.IEEE transactions on pattern analysis and machine intelligence, 43(10):3614–3631, 2020

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:30.842534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 33f60f79-452f-427d-ab6e-a14bb27779a4 · outbound

This paper cites Singular value decomposition and least squares solutions.

Generalized Category Discovery via Token Manifold Capacity Learning Singular value decomposition and least squares solutions

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:30.671638Z

Source-reported events for the cited work

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Observation 19c0563d-66c7-41dd-843a-9ef8ca0a484d · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284, 2020.

Generalized Category Discovery via Token Manifold Capacity Learning Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284, 2020

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:30.460868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f6263e1b-affa-47f2-acb6-29b5348f61a9 · outbound

This paper cites Pre-training with Random Orthogonal Projection Image Modeling.

Generalized Category Discovery via Token Manifold Capacity Learning Pre-training with Random Orthogonal Projection Image Modeling

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:43:19.655494Z

Source-reported events for the cited work

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Observation 352fe3b2-31b3-43da-a9d6-313b5b7ace31 · outbound

This paper cites Automatically Discovering and Learning New Visual Categories with Ranking Statistics.

Generalized Category Discovery via Token Manifold Capacity Learning Automatically Discovering and Learning New Visual Categories with Ranking Statistics

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:14.023471Z

Source-reported events for the cited work

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Observation 75a20a8b-4702-455b-b4e9-667dedb17eb8 · outbound

This paper cites Learning to discover novel visual categories via deep transfer clustering.

Generalized Category Discovery via Token Manifold Capacity Learning Learning to discover novel visual categories via deep transfer clustering

Reference 22

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Source-reported events for the cited work

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Observation 983d4dbe-6436-404e-86a0-5cc18c79c0db · outbound

This paper cites On feature decorrelation in self-supervised learning.

Generalized Category Discovery via Token Manifold Capacity Learning On feature decorrelation in self-supervised learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:30.249883Z

Source-reported events for the cited work

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Observation d2a7136e-2119-461a-b681-c300924f693d · outbound

This paper cites An information-theoretic understanding of maximum manifold capacity representations.

Generalized Category Discovery via Token Manifold Capacity Learning An information-theoretic understanding of maximum manifold capacity representations

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:26.197994Z

Source-reported events for the cited work

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Observation 4047cf20-54f1-46b8-818f-f0a1fd3762a2 · outbound

This paper cites Understanding Dimensional Collapse in Contrastive Self-supervised Learning.

Generalized Category Discovery via Token Manifold Capacity Learning Understanding Dimensional Collapse in Contrastive Self-supervised Learning

Reference 25

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Source-reported events for the cited work

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Observation bee16fc4-5df3-43f2-ad31-fc0fbfe3abc9 · outbound

This paper cites Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673, 2020.

Generalized Category Discovery via Token Manifold Capacity Learning Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673, 2020

Reference 26

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Source-reported events for the cited work

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Observation d256038b-a4c9-447f-9dc7-8e3258a97edb · outbound

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

Generalized Category Discovery via Token Manifold Capacity Learning 3d object representations for fine-grained categorization

Reference 27

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Observation c5421bde-4a54-4a1d-8fa7-490a4405e582 · outbound

This paper cites Cifar-10 dataset.

Generalized Category Discovery via Token Manifold Capacity Learning Cifar-10 dataset

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:25.739725Z

Source-reported events for the cited work

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Observation 0d2bf732-8370-441c-8853-cc9cf63b7fec · outbound

This paper cites The hungarian method for the assignment problem.Naval research logistics quarterly, 2(1-2):83–97, 1955.

Generalized Category Discovery via Token Manifold Capacity Learning The hungarian method for the assignment problem.Naval research logistics quarterly, 2(1-2):83–97, 1955

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:14.863851Z

Source-reported events for the cited work

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Observation b72d61ea-18ea-4e2f-8dff-03e04ae42343 · outbound

This paper cites Sphereface: Deep hypersphere embedding for face recognition.

Generalized Category Discovery via Token Manifold Capacity Learning Sphereface: Deep hypersphere embedding for face recognition

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:14.969510Z

Source-reported events for the cited work

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Observation f009d266-53d5-461f-af7c-8520d34ebe2e · outbound

This paper cites A frobenius norm approach to glottal closure detection from the speech signal.IEEE Transactions on Speech and Audio Processing, 2(2):258–265, 1994.

Generalized Category Discovery via Token Manifold Capacity Learning A frobenius norm approach to glottal closure detection from the speech signal.IEEE Transactions on Speech and Audio Processing, 2(2):258–265, 1994

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:25.535499Z

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Observation 918775c9-1ffb-457e-b15c-1d2c3a406554 · outbound

This paper cites Protogcd: Unified and unbiased prototype learning for generalized category discovery.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.

Generalized Category Discovery via Token Manifold Capacity Learning Protogcd: Unified and unbiased prototype learning for generalized category discovery.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:25.194943Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c93afa51-785a-492a-a394-b3aafcf909f4 · outbound

This paper cites Happy: A Debiased Learning Framework for Continual Generalized Category Discovery.

Generalized Category Discovery via Token Manifold Capacity Learning Happy: A Debiased Learning Framework for Continual Generalized Category Discovery

Reference 33

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Observation b858bf71-6f35-4ea7-be32-f0d22ae24360 · outbound

This paper cites Active generalized category discovery.

Generalized Category Discovery via Token Manifold Capacity Learning Active generalized category discovery

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:24.817754Z

Source-reported events for the cited work

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Observation 3d38d371-0e37-48a9-bd87-557a1b3459ae · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Generalized Category Discovery via Token Manifold Capacity Learning Fine-Grained Visual Classification of Aircraft

Reference 35

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Observation cdb25749-5795-468d-97a9-5baf4b10e36e · outbound

This paper cites Inequalities: Theory of majorization and its applications, 1979.

Generalized Category Discovery via Token Manifold Capacity Learning Inequalities: Theory of majorization and its applications, 1979

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:24.654040Z

Source-reported events for the cited work

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Observation 7b4eda0f-193c-4d6a-af3a-01d2a827db4d · outbound

This paper cites Hyperspherical prototype networks.Advances in neural information processing systems, 32, 2019.

Generalized Category Discovery via Token Manifold Capacity Learning Hyperspherical prototype networks.Advances in neural information processing systems, 32, 2019

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:15.781745Z

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Observation c776a0e6-780e-48ea-a982-0654e199bbdc · outbound

This paper cites Self-supervised learning with an information maximization criterion.

Generalized Category Discovery via Token Manifold Capacity Learning Self-supervised learning with an information maximization criterion

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:24.356434Z

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Observation 2af932cd-689d-4f31-b2cc-caa723783c6d · outbound

This paper cites Deep face recognition.

Generalized Category Discovery via Token Manifold Capacity Learning Deep face recognition

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:24.003835Z

Source-reported events for the cited work

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Observation a2d3516f-21d9-4eff-bb34-af5d8bbb35a1 · outbound

This paper cites Connections between nuclear-norm and frobenius- norm-based representations.IEEE transactions on neural networks and learning systems, 29(1):218–224, 2016.

Generalized Category Discovery via Token Manifold Capacity Learning Connections between nuclear-norm and frobenius- norm-based representations.IEEE transactions on neural networks and learning systems, 29(1):218–224, 2016

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:23.733608Z

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Observation cc64dfb5-9311-4542-a6a7-790c5204f207 · outbound

This paper cites Entropy, von neumann and the von neumann entropy: Dedicated to the memory of alfred wehrl.

Generalized Category Discovery via Token Manifold Capacity Learning Entropy, von neumann and the von neumann entropy: Dedicated to the memory of alfred wehrl

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:23.526830Z

Source-reported events for the cited work

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Observation 9f16d9fa-0438-4b3c-b76c-92b300998452 · outbound

This paper cites Dynamic conceptional contrastive learning for generalized category discovery.

Generalized Category Discovery via Token Manifold Capacity Learning Dynamic conceptional contrastive learning for generalized category discovery

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:23.316840Z

Source-reported events for the cited work

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Observation f33e1532-57ec-4801-93e5-398e595ad6bc · outbound

This paper cites Machine learning: Algorithms, real-world applications and research directions.SN computer science, 2(3):160, 2021.

Generalized Category Discovery via Token Manifold Capacity Learning Machine learning: Algorithms, real-world applications and research directions.SN computer science, 2(3):160, 2021

Reference 43

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Observation 13ac31b9-42ed-43ed-8f9d-b099f1d3e680 · outbound

This paper cites Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations.

Generalized Category Discovery via Token Manifold Capacity Learning Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:16.566959Z

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Observation 66739f38-d770-42cc-9782-841f7f402bcd · outbound

This paper cites Understanding and mitigating dimensional collapse in federated learning.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

Generalized Category Discovery via Token Manifold Capacity Learning Understanding and mitigating dimensional collapse in federated learning.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:23.113248Z

Source-reported events for the cited work

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Observation 42a658d4-0cc8-46fd-b7a1-f2a6b02c2abb · outbound

This paper cites Manifold clustering.

Generalized Category Discovery via Token Manifold Capacity Learning Manifold clustering

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:22.943227Z

Source-reported events for the cited work

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Observation bbb2c9d5-1ac0-49a8-ba15-e4d16a692589 · outbound

This paper cites The Herbarium Challenge 2019 Dataset.

Generalized Category Discovery via Token Manifold Capacity Learning The Herbarium Challenge 2019 Dataset

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:17.014284Z

Source-reported events for the cited work

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Observation 29ede7ff-c097-4a90-8f98-ec3a17eb03eb · outbound

This paper cites Breaking the curse of dimensional collapse in graph contrastive learning: A whitening perspective.Information Sciences, 657:119952, 2024.

Generalized Category Discovery via Token Manifold Capacity Learning Breaking the curse of dimensional collapse in graph contrastive learning: A whitening perspective.Information Sciences, 657:119952, 2024

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:22.762621Z

Source-reported events for the cited work

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Observation b4a7b985-c02f-444e-ac18-c07ce22a291e · outbound

This paper cites Wiley-Interscience, 2006.

Generalized Category Discovery via Token Manifold Capacity Learning Wiley-Interscience, 2006

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:22.585662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1093c9e6-8d15-49aa-a084-76ddb0451b2c · outbound

This paper cites Generalized category discovery.

Generalized Category Discovery via Token Manifold Capacity Learning Generalized category discovery

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:22.394336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 629bfd48-a2af-4130-9dd8-43908d77e7c8 · outbound

This paper cites Open-set recognition: A good closed-set classifier is all you need.

Generalized Category Discovery via Token Manifold Capacity Learning Open-set recognition: A good closed-set classifier is all you need

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:22.170783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f30bddcb-5b04-4c15-9994-2f5546a8d616 · outbound

This paper cites Cambridge university press, 2018.

Generalized Category Discovery via Token Manifold Capacity Learning Cambridge university press, 2018

Reference 52

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Generalized Category Discovery via Token Manifold Capacity Learning Unresolved cited work

Reference 53

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This paper cites Understanding contrastive representation learning through alignment and uniformity on the hypersphere.

Generalized Category Discovery via Token Manifold Capacity Learning Understanding contrastive representation learning through alignment and uniformity on the hypersphere

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:17.874745Z

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This paper cites Hierarchical grouping to optimize an objective function.Journal of the American statistical association, 58(301):236–244, 1963.

Generalized Category Discovery via Token Manifold Capacity Learning Hierarchical grouping to optimize an objective function.Journal of the American statistical association, 58(301):236–244, 1963

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:17.974882Z

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This paper cites A survey of transfer learning.Journal of Big data, 3:1–40, 2016.

Generalized Category Discovery via Token Manifold Capacity Learning A survey of transfer learning.Journal of Big data, 3:1–40, 2016

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:18.063835Z

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This paper cites Parametric classification for generalized category discovery: A baseline study.

Generalized Category Discovery via Token Manifold Capacity Learning Parametric classification for generalized category discovery: A baseline study

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:21.760730Z

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This paper cites Towards open vocabulary learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024.

Generalized Category Discovery via Token Manifold Capacity Learning Towards open vocabulary learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:21.584802Z

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This paper cites Regularizing deep convolutional neural networks with a structured decorrelation constraint.

Generalized Category Discovery via Token Manifold Capacity Learning Regularizing deep convolutional neural networks with a structured decorrelation constraint

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:21.349596Z

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This paper cites Learning efficient coding of natural images with maximum manifold capacity representations.Advances in Neural Information Processing Systems, 36:24103–24128, 2023.

Generalized Category Discovery via Token Manifold Capacity Learning Learning efficient coding of natural images with maximum manifold capacity representations.Advances in Neural Information Processing Systems, 36:24103–24128, 2023

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:21.112718Z

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

Generalized Category Discovery via Token Manifold Capacity Learning Barlow twins: Self-supervised learning via redundancy reduction

Reference 61

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This paper cites Promptcal: Contrastive affinity learning via auxiliary prompts for generalized novel category discovery.

Generalized Category Discovery via Token Manifold Capacity Learning Promptcal: Contrastive affinity learning via auxiliary prompts for generalized novel category discovery

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:20.662470Z

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Generalized Category Discovery via Token Manifold Capacity Learning Geometric view of soft decorrelation in self-supervised learning

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:20.465632Z

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This paper cites Learning semi-supervised gaussian mixture models for generalized category discovery.

Generalized Category Discovery via Token Manifold Capacity Learning Learning semi-supervised gaussian mixture models for generalized category discovery

Reference 64

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This paper cites Domain generalization: A survey.

Generalized Category Discovery via Token Manifold Capacity Learning Domain generalization: A survey

Reference 65

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Pith citing papers

Observation ac13950b-3760-44fd-8c72-fcbc69f996ee · inbound

SpectralGCD: Spectral Concept Selection and Cross-modal Representation Learning for Generalized Category Discovery cites this paper.

SpectralGCD: Spectral Concept Selection and Cross-modal Representation Learning for Generalized Category Discovery Generalized Category Discovery via Token Manifold Capacity Learning

Reference 10

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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 Generalized Category Discovery via Token Manifold Capacity Learning

Reference 147

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