Long-Tailed Learning for Generalized Category Discovery | Paper Citation Record

Observation 68c287df-a891-4eaf-9b1a-3156ba95df15 · outbound

This paper cites Masked siamese networks for label-efficient learning, in: European conference on computer vision, Springer.

Long-Tailed Learning for Generalized Category Discovery Masked siamese networks for label-efficient learning, in: European conference on computer vision, Springer

Reference 1

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Observation 7e53f2a4-c4c0-4df0-b159-1c2284a004d4 · outbound

This paper cites Towards distribution-agnostic generalized cate- gory discovery.

Long-Tailed Learning for Generalized Category Discovery Towards distribution-agnostic generalized cate- gory discovery

Reference 2

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Observation 8146bfef-6bae-40b4-97b8-2f8675cbeed6 · outbound

This paper cites Open- world semi-supervised learning, in: International Confer- ence on Learning Representations, pp.

Long-Tailed Learning for Generalized Category Discovery Open- world semi-supervised learning, in: International Confer- ence on Learning Representations, pp

Reference 3

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This paper cites Learning imbalanced datasets with label-distribution-aware margin loss.

Long-Tailed Learning for Generalized Category Discovery Learning imbalanced datasets with label-distribution-aware margin loss

Reference 4

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Observation cb8bb6c9-7849-4548-938e-f9e48038f0dd · outbound

This paper cites Emerging properties in self-supervised vision trans- formers, in: Proceedings of the IEEE /CVF international conference on computer vision, pp.

Long-Tailed Learning for Generalized Category Discovery Emerging properties in self-supervised vision trans- formers, in: Proceedings of the IEEE /CVF international conference on computer vision, pp

Reference 5

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This paper cites Smote: synthetic minority over-sampling technique.

Long-Tailed Learning for Generalized Category Discovery Smote: synthetic minority over-sampling technique

Reference 6

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Long-Tailed Learning for Generalized Category Discovery Unresolved cited work

Reference 7

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This paper cites Class- balanced loss based on e ffective number of samples, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Long-Tailed Learning for Generalized Category Discovery Class- balanced loss based on e ffective number of samples, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 8

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Observation 20eadbc4-dd72-45e5-81d5-c7ed5e43f99a · outbound

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

Long-Tailed Learning for Generalized Category Discovery Sinkhorn distances: Lightspeed computation of optimal transport

Reference 9

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Observation 03bf06e0-ade9-4436-a705-4ab82b56421e · outbound

This paper cites LPT: Long-tailed prompt tuning for image classification, in: The Eleventh International Conference on Learning Representations, pp.

Long-Tailed Learning for Generalized Category Discovery LPT: Long-tailed prompt tuning for image classification, in: The Eleventh International Conference on Learning Representations, pp

Reference 10

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Long-Tailed Learning for Generalized Category Discovery Unresolved cited work

Reference 11

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Observation bcf4d4d7-fb4f-4ff7-bb31-73465cf323bf · outbound

This paper cites Learning to discover and detect objects.

Long-Tailed Learning for Generalized Category Discovery Learning to discover and detect objects

Reference 12

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Observation 7c6209b4-1244-4c93-9228-2400f51cfbd1 · outbound

This paper cites Enhancing minority classes by mixing: An adaptative optimal transport approach for long-tailed classifi- cation.

Long-Tailed Learning for Generalized Category Discovery Enhancing minority classes by mixing: An adaptative optimal transport approach for long-tailed classifi- cation

Reference 13

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Observation 726ee2dc-1c88-4c62-85f5-1852069fda82 · outbound

This paper cites Autonovel: Automatically discovering and learning novel visual cate- gories.

Long-Tailed Learning for Generalized Category Discovery Autonovel: Automatically discovering and learning novel visual cate- gories

Reference 14

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This paper cites Momentum contrast for unsupervised visual representation learning, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Long-Tailed Learning for Generalized Category Discovery Momentum contrast for unsupervised visual representation learning, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 15

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This paper cites Learning to cluster in order to trans- fer across domains and tasks, in: International Conference on Learning Representations, pp.

Long-Tailed Learning for Generalized Category Discovery Learning to cluster in order to trans- fer across domains and tasks, in: International Conference on Learning Representations, pp

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.965439Z

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Observation e2bcda25-ff0e-47cf-8a35-6cd3ad3d66b6 · outbound

This paper cites Learning discrete representations via information maximizing self- augmented training, in: International conference on machine learning, PMLR.

Long-Tailed Learning for Generalized Category Discovery Learning discrete representations via information maximizing self- augmented training, in: International conference on machine learning, PMLR

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.956662Z

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This paper cites Self-damaging contrastive learning, in: International Conference on Machine Learning, PMLR.

Long-Tailed Learning for Generalized Category Discovery Self-damaging contrastive learning, in: International Conference on Machine Learning, PMLR

Reference 18

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Long-Tailed Learning for Generalized Category Discovery Unresolved cited work

Reference 19

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Observation c66c0a6d-9ab9-4fc3-93b0-dd6decab0f88 · outbound

This paper cites Decoupling representation and classifier for long-tailed recog- nition, in: Eighth International Conference on Learning Representations (ICLR), pp.

Long-Tailed Learning for Generalized Category Discovery Decoupling representation and classifier for long-tailed recog- nition, in: Eighth International Conference on Learning Representations (ICLR), pp

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.930559Z

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Observation 828854f8-1eb9-4bf5-931c-501ad5ad8788 · outbound

This paper cites Distri- bution aligning refinery of pseudo-label for imbalanced semi-supervised learning.

Long-Tailed Learning for Generalized Category Discovery Distri- bution aligning refinery of pseudo-label for imbalanced semi-supervised learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.921441Z

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This paper cites M2m: Imbalanced classification via major-to-minor translation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Long-Tailed Learning for Generalized Category Discovery M2m: Imbalanced classification via major-to-minor translation, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.911399Z

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Observation 611d4475-42f5-4c77-9843-f63a7a87f60e · outbound

This paper cites Temperature schedules for self-supervised contrastive methods on long-tail data, in: ICLR, pp.

Long-Tailed Learning for Generalized Category Discovery Temperature schedules for self-supervised contrastive methods on long-tail data, in: ICLR, pp

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.901535Z

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This paper cites Abc: Auxiliary balanced classifier for class-imbalanced semi-supervised learning.

Long-Tailed Learning for Generalized Category Discovery Abc: Auxiliary balanced classifier for class-imbalanced semi-supervised learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.892421Z

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Observation eb350ee5-520d-4dcf-ba1c-5d042a183449 · outbound

This paper cites Long-tailed visual recognition via gaussian clouded logit adjustment, in: Proceedings of the IEEE/CVF con- ference on computer vision and pattern recognition, pp.

Long-Tailed Learning for Generalized Category Discovery Long-tailed visual recognition via gaussian clouded logit adjustment, in: Proceedings of the IEEE/CVF con- ference on computer vision and pattern recognition, pp

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.883131Z

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Observation 5f954e10-440f-492d-bc7f-924236cf1b0d · outbound

This paper cites Im- proving visual prompt tuning by gaussian neighborhood minimization for long-tailed visual recognition.

Long-Tailed Learning for Generalized Category Discovery Im- proving visual prompt tuning by gaussian neighborhood minimization for long-tailed visual recognition

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.873628Z

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Observation 3c1791b3-0cca-4def-8539-195cc062b996 · outbound

This paper cites Feature fusion from head to tail for long-tailed visual recognition, in: Proceedings of the AAAI conference on artificial intelligence, pp.

Long-Tailed Learning for Generalized Category Discovery Feature fusion from head to tail for long-tailed visual recognition, in: Proceedings of the AAAI conference on artificial intelligence, pp

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.864361Z

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This paper cites Conmix: Contrastive mixup at representa- tion level for long-tailed deep clustering, in: The Thirteenth Interna- tional Conference on Learning Representations, pp.

Long-Tailed Learning for Generalized Category Discovery Conmix: Contrastive mixup at representa- tion level for long-tailed deep clustering, in: The Thirteenth Interna- tional Conference on Learning Representations, pp

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.855073Z

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Observation b4305ca1-6d4b-4600-9bab-373815f8848f · outbound

This paper cites Exploratory undersampling for class- imbalance learning.

Long-Tailed Learning for Generalized Category Discovery Exploratory undersampling for class- imbalance learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.845673Z

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Observation c6a8518d-e958-4bf5-9707-d97f3d0727df · outbound

This paper cites Large- scale long-tailed recognition in an open world, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Long-Tailed Learning for Generalized Category Discovery Large- scale long-tailed recognition in an open world, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.836059Z

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Observation 27f851ae-6365-4a07-8377-692419b22e16 · outbound

This paper cites Protogcd: Uni- fied and unbiased prototype learning for generalized category discov- ery.

Long-Tailed Learning for Generalized Category Discovery Protogcd: Uni- fied and unbiased prototype learning for generalized category discov- ery

Reference 31

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Observation 544bfb15-16e1-4f7a-a7df-fc252a38ff3f · outbound

This paper cites One million scenes for autonomous driving: Once dataset.

Long-Tailed Learning for Generalized Category Discovery One million scenes for autonomous driving: Once dataset

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.827102Z

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This paper cites Fighting class imbalance with contrastive learning, in: International conference on medical image computing and computer-assisted intervention, Springer.

Long-Tailed Learning for Generalized Category Discovery Fighting class imbalance with contrastive learning, in: International conference on medical image computing and computer-assisted intervention, Springer

Reference 33

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Long-Tailed Learning for Generalized Category Discovery Unresolved cited work

Reference 34

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Observation 0cefd5f5-42d3-4297-8b20-948f459ddcf5 · outbound

This paper cites Towards realistic semi- supervised learning, in: European Conference on Computer Vision, Springer.

Long-Tailed Learning for Generalized Category Discovery Towards realistic semi- supervised learning, in: European Conference on Computer Vision, Springer

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.799390Z

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Observation 2769401b-c149-45d4-97d3-a42d2e677f8e · outbound

This paper cites Long- tail learning with foundation model: Heavy fine-tuning hurts, in: Interna- tional Conference on Machine Learning, PMLR.

Long-Tailed Learning for Generalized Category Discovery Long- tail learning with foundation model: Heavy fine-tuning hurts, in: Interna- tional Conference on Machine Learning, PMLR

Reference 36

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This paper cites Opencon: Open-world contrastive learning, in: Transactions on Machine Learning Research, pp.

Long-Tailed Learning for Generalized Category Discovery Opencon: Open-world contrastive learning, in: Transactions on Machine Learning Research, pp

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.780332Z

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This paper cites Equalization loss for long-tailed object recognition, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Long-Tailed Learning for Generalized Category Discovery Equalization loss for long-tailed object recognition, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.771273Z

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Observation 2dc76e2d-2daf-418e-bf00-188b2dc4c969 · outbound

This paper cites Contrastive multiview coding, in: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XI 16, Springer.

Long-Tailed Learning for Generalized Category Discovery Contrastive multiview coding, in: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XI 16, Springer

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.762119Z

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Observation 8a074049-f35a-4705-8ce5-1286f4740caf · outbound

This paper cites The inaturalist species classi- fication and detection dataset, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp.

Long-Tailed Learning for Generalized Category Discovery The inaturalist species classi- fication and detection dataset, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.752596Z

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Observation 5b774d93-00b9-4035-b511-fcf88adb75bb · outbound

This paper cites Generalized category discovery, in: Proceedings of the IEEE /CVF Conference on Computer Vision and Pattern Recognition, pp.

Long-Tailed Learning for Generalized Category Discovery Generalized category discovery, in: Proceedings of the IEEE /CVF Conference on Computer Vision and Pattern Recognition, pp

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.743097Z

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Observation 217a887e-957b-43d7-befb-8f8de11c5ddf · outbound

This paper cites Adap- tive class suppression loss for long-tail object detection, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Long-Tailed Learning for Generalized Category Discovery Adap- tive class suppression loss for long-tail object detection, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.732839Z

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This paper cites Parametric classification for generalized category discovery: A baseline study, in: Proceedings of the IEEE /CVF International Conference on Computer Vision, pp.

Long-Tailed Learning for Generalized Category Discovery Parametric classification for generalized category discovery: A baseline study, in: Proceedings of the IEEE /CVF International Conference on Computer Vision, pp

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.722194Z

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Observation 9f5d5889-de8a-40d8-856b-41b189563a93 · outbound

This paper cites Divide and con- quer: Compositional experts for generalized novel class discovery, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pat- tern Recognition, pp.

Long-Tailed Learning for Generalized Category Discovery Divide and con- quer: Compositional experts for generalized novel class discovery, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pat- tern Recognition, pp

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.711281Z

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Observation 6522ae5f-c70f-4981-9bdf-3b7bbcbfbe39 · outbound

This paper cites Novel class discovery for long-tailed recognition.

Long-Tailed Learning for Generalized Category Discovery Novel class discovery for long-tailed recognition

Reference 45

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Observation 8a4316e8-968a-4ce1-8f1c-6b5f8e53edd5 · outbound

This paper cites Deep long-tailed learning: A survey.

Long-Tailed Learning for Generalized Category Discovery Deep long-tailed learning: A survey

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.691277Z

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Observation c3552f9b-aaca-43cd-8ac2-cfa34881a86e · outbound

This paper cites Improving calibration for long- tailed recognition, in: Proceedings of the IEEE/CVF conference on com- puter vision and pattern recognition, pp.

Long-Tailed Learning for Generalized Category Discovery Improving calibration for long- tailed recognition, in: Proceedings of the IEEE/CVF conference on com- puter vision and pattern recognition, pp

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.681615Z

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Observation f96702e3-610b-4ad2-a7ed-997675603377 · outbound

This paper cites Bbn: Bilateral-branch network with cumulative learning for long-tailed visual recognition, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp.

Long-Tailed Learning for Generalized Category Discovery Bbn: Bilateral-branch network with cumulative learning for long-tailed visual recognition, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.671546Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2a2e64bf-c87f-4ca5-ad4f-c65894ebe3d7 · outbound

This paper cites Places: A 10 million image database for scene recognition.

Long-Tailed Learning for Generalized Category Discovery Places: A 10 million image database for scene recognition

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:36.660691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 53cc5171-426b-4512-ac11-46c5e97a2956 · outbound

This paper cites 9284– 9292.

Long-Tailed Learning for Generalized Category Discovery 9284– 9292

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:51:37.008908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers