Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning | Paper Citation Record

Observation 5b75921c-ca1d-4e8a-a937-2b15e155ce12 · outbound

This paper cites Online continual learning with maximal interfered retrieval.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Online continual learning with maximal interfered retrieval

Reference 1

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Observation f5247d42-eb49-422b-ba98-76cb55fdd7c6 · outbound

This paper cites Gradient based sample selection for online continual learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Gradient based sample selection for online continual learning

Reference 2

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Observation 4b9afa39-0a9d-4fe7-9030-272d42fdc0a2 · outbound

This paper cites New insights on reducing abrupt representation change in online continual learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning New insights on reducing abrupt representation change in online continual learning

Reference 3

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Observation 0aa835e0-74b9-44fe-9be8-4daf3ce49628 · outbound

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

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Emerging properties in self-supervised vision transformers

Reference 4

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Observation c959a120-bc53-4973-bfbb-43f8ad256930 · outbound

This paper cites Co2l: Contrastive continual learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Co2l: Contrastive continual learning

Reference 5

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Observation ab90e5ec-3a80-4953-b592-4ab53668e539 · outbound

This paper cites Efficient lifelong learning with a-gem.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Efficient lifelong learning with a-gem

Reference 6

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Observation 2dbda706-8b34-4e3c-af25-24d7ada855e4 · outbound

This paper cites On Tiny Episodic Memories in Continual Learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning On Tiny Episodic Memories in Continual Learning

Reference 7

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Observation 7b6f5816-3863-4f36-a66b-e5cb2932a248 · outbound

This paper cites Continual learning in low-rank orthogonal subspaces.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Continual learning in low-rank orthogonal subspaces

Reference 8

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Observation b54574ab-4e6e-46df-a173-6fa745e65428 · outbound

This paper cites Learning semantic-specific graph representation for multi-label image recognition.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Learning semantic-specific graph representation for multi-label image recognition

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:56.591519Z

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Observation 373500a8-422b-469a-a67c-f3c59413a047 · outbound

This paper cites Improved Baselines with Momentum Contrastive Learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Improved Baselines with Momentum Contrastive Learning

Reference 10

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Observation 694a59dd-5a4d-40fa-8b3a-53c6246972b8 · outbound

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

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning An Empirical Study of Training Self-Supervised Vision Transformers

Reference 11

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This paper cites Nus-wide: a real-world web image database from national university of singapore.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Nus-wide: a real-world web image database from national university of singapore

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:56.422449Z

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Observation 85c4ecf5-1f3d-48af-92e5-e5dbf827e751 · outbound

This paper cites an unresolved cited work.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Unresolved cited work

Reference 13

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Observation ae61f3ef-dbde-4756-b73a-6c262dae3937 · outbound

This paper cites Vision Transformers Need Registers.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Vision Transformers Need Registers

Reference 14

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Observation f70d253c-3bd4-44f7-bcf5-acf1c3774203 · outbound

This paper cites Knowledge restore and transfer for multi-label class-incremental learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Knowledge restore and transfer for multi-label class-incremental learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:56.222605Z

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Observation 04e9c48d-0ee9-434d-969d-e359e4806a0b · outbound

This paper cites Agcn: augmented graph convolutional network for lifelong multi-label image recognition.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Agcn: augmented graph convolutional network for lifelong multi-label image recognition

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:56.035458Z

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Observation dc47fbf7-1676-438c-baca-f09a9392e65a · outbound

This paper cites Multi-label continual learning using augmented graph convolutional network.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Multi-label continual learning using augmented graph convolutional network

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:55.890782Z

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Observation 258eea80-0a58-40db-ba4c-14f5f03d0d37 · outbound

This paper cites Rebalancing Multi-Label Class-Incremental Learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Rebalancing Multi-Label Class-Incremental Learning

Reference 18

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Observation fe07941c-c6e8-4bb4-a731-c28ea5dced5e · outbound

This paper cites Confidence self-calibration for multi-label class-incremental learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Confidence self-calibration for multi-label class-incremental learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:55.797806Z

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Observation 053d717f-7c6f-4b3f-b43d-5904b90fe7dc · outbound

This paper cites A., Van Gool, L., Williams, C.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning A., Van Gool, L., Williams, C

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:55.669874Z

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Observation 47723213-6b20-41ab-ab24-77c7539e02e3 · outbound

This paper cites and Zhou, H.-Y.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning and Zhou, H.-Y

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:55.551383Z

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Observation a811d609-59a7-4163-b6af-fb10985e44ee · outbound

This paper cites A., Prabhu, A., Torr, P.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning A., Prabhu, A., Torr, P

Reference 22

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Observation 930255e9-458d-4c96-92d4-043f063be2ee · outbound

This paper cites Not just selection, but exploration: Online class-incremental continual learning via dual view consistency.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Not just selection, but exploration: Online class-incremental continual learning via dual view consistency

Reference 23

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Observation 28f1de28-69d9-4c25-b9d6-b5bfcd071c5a · outbound

This paper cites M., and Bifet, A.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning M., and Bifet, A

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:55.189406Z

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Observation b8468821-5114-40c7-bcf6-5d24ce44e833 · outbound

This paper cites Online continual learning through mutual information maximization.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Online continual learning through mutual information maximization

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:55.019480Z

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Observation c9937c22-a6a9-434f-a9d5-1eb17afa8876 · outbound

This paper cites and Zhang, M.-L.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning and Zhang, M.-L

Reference 26

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Observation d8cb020c-8ffe-45f6-ae2b-81f50f766168 · outbound

This paper cites and Zhang, M.-L.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning and Zhang, M.-L

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:54.383714Z

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Observation 33c46847-8c35-4b29-8daa-9f4bda019851 · outbound

This paper cites End-to-end probabilistic label-specific feature learning for multi-label classification.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning End-to-end probabilistic label-specific feature learning for multi-label classification

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:54.105191Z

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Observation 029ea2b9-7b75-4bef-9267-81a2bcba3dc2 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Momentum contrast for unsupervised visual representation learning

Reference 29

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This paper cites Masked autoencoders are scalable vision learners.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Masked autoencoders are scalable vision learners

Reference 30

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Observation 429943ec-e5a8-4929-919c-5bbe6543ad70 · outbound

This paper cites Learning label specific features for multi-label classification.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Learning label specific features for multi-label classification

Reference 31

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Observation f9d11460-d686-4542-9211-1c0ad6bddab3 · outbound

This paper cites Learning label-specific features and class-dependent labels for multi-label classification.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Learning label-specific features and class-dependent labels for multi-label classification

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:53.630136Z

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Observation 6ed6d6bb-66bb-4b33-9ddd-33eb2e60f12a · outbound

This paper cites D., Jeong, J., and Kim, G.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning D., Jeong, J., and Kim, G

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:53.487686Z

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Observation 772acf73-b2b5-40eb-99be-4b1ff553bd6c · outbound

This paper cites Learning common and label-specific features for multi-label classification with correlation information.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Learning common and label-specific features for multi-label classification with correlation information

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:53.220788Z

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Observation a6643d57-da0b-4bcf-8a5b-47a1ee2e0915 · outbound

This paper cites Patchct: Aligning patch set and label set with conditional transport for multi-label image classification.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Patchct: Aligning patch set and label set with conditional transport for multi-label image classification

Reference 35

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Observation 30f1315b-19e3-4033-99bf-a17c04d08fcc · outbound

This paper cites A Survey on Incomplete Multi-label Learning: Recent Advances and Future Trends.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning A Survey on Incomplete Multi-label Learning: Recent Advances and Future Trends

Reference 36

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Observation 39789151-3d91-4b7f-9365-9888af294dd6 · outbound

This paper cites Pushing one pair of labels apart each time in multi-label learning: from single positive to full labels.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Pushing one pair of labels apart each time in multi-label learning: from single positive to full labels

Reference 37

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Observation dbd9e397-9f50-4fb6-96e2-fedf69e6d075 · outbound

This paper cites Optimizing Class Distribution in Memory for Multi-Label Online Continual Learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Optimizing Class Distribution in Memory for Multi-Label Online Continual Learning

Reference 38

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Observation 75f13584-bef6-4000-9a82-3bdfe16656b9 · outbound

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Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Unresolved cited work

Reference 39

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Observation e94184b9-f376-4e5b-8174-db60d5a644a4 · outbound

This paper cites Supervised contrastive replay: Revisiting the nearest class mean classifier in online class-incremental continual learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Supervised contrastive replay: Revisiting the nearest class mean classifier in online class-incremental continual learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:52.567695Z

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Observation ef88ac24-a0a7-40c7-8e6d-719a917a07ec · outbound

This paper cites S., Shao, L., and Shah, M.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning S., Shao, L., and Shah, M

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:52.367446Z

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Observation 861002b2-7bb6-4301-9d49-7da3c7cc9c93 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning DINOv2: Learning Robust Visual Features without Supervision

Reference 42

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Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Unresolved cited work

Reference 43

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Observation 9e261d66-cbea-4041-9847-8b029cbc1a73 · outbound

This paper cites Label distribution learning with label-specific features.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Label distribution learning with label-specific features

Reference 44

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Observation b98e30ff-bdf1-4d8b-a525-18c3d5d55792 · outbound

This paper cites Asymmetric loss for multi-label classification.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Asymmetric loss for multi-label classification

Reference 45

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Observation 56adc313-6cd4-4278-b1a5-d8997f583306 · outbound

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Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Unresolved cited work

Reference 46

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Observation 5f135fd2-e436-4dc4-b7d1-b450fd6260ec · outbound

This paper cites R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., and Batra, D.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., and Batra, D

Reference 47

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This paper cites and Malik, J.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning and Malik, J

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:51.552960Z

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Observation e68d9824-d1a7-401e-bde7-f97cde21234e · outbound

This paper cites Online class-incremental continual learning with adversarial shapley value.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Online class-incremental continual learning with adversarial shapley value

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:51.386162Z

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Observation 05451cd3-5772-489b-8227-d60c95f4df9e · outbound

This paper cites Localizing Objects with Self-Supervised Transformers and no Labels.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Localizing Objects with Self-Supervised Transformers and no Labels

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T14:14:44.179501Z

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Observation 7bfbe354-f34b-4bf7-8875-dba7596fb39e · outbound

This paper cites Overcoming catastrophic forgetting for multi-label class-incremental learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Overcoming catastrophic forgetting for multi-label class-incremental learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:51.212963Z

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Observation ac12a885-1552-40da-8547-f20abf2b06fe · outbound

This paper cites Memory replay with data compression for continual learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Memory replay with data compression for continual learning

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:50.945578Z

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Observation bd9ae44a-2f29-4812-bc2f-29ba33234043 · outbound

This paper cites X., and Misra, I.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning X., and Misra, I

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:50.738600Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 94bd6e62-e60d-4130-9df5-fbd04cec1083 · outbound

This paper cites X., Crowley, J.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning X., Crowley, J

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:50.470546Z

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.

Observation 301584b8-01c6-4d6b-9e95-7800fbd296f1 · outbound

This paper cites Multi-label image recognition by recurrently discovering attentional regions.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Multi-label image recognition by recurrently discovering attentional regions

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:50.241964Z

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.

Observation 2d866214-baaf-4157-b185-9c0f6067e401 · outbound

This paper cites and Li, Y.-F.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning and Li, Y.-F

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:50.066627Z

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.

Observation 8d634dd7-a8e3-41fd-ac09-e888f67bedd1 · outbound

This paper cites and Li, Y.-F.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning and Li, Y.-F

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:49.861818Z

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.

Observation 4007899a-689a-4093-bfd8-2027249213fb · outbound

This paper cites Learning safe multi-label prediction for weakly labeled data.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Learning safe multi-label prediction for weakly labeled data

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:49.643147Z

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.

Observation 1b582d1e-c27f-4faf-87a8-b0b648405bc6 · outbound

This paper cites Probabilistic label tree for streaming multi-label learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Probabilistic label tree for streaming multi-label learning

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:49.360770Z

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.

Observation b6cfe17a-b2ed-4e20-9e0c-5469e77072ba · outbound

This paper cites Online prototype learning for online continual learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Online prototype learning for online continual learning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:49.166924Z

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.

Observation 3469c34c-9b0f-4085-b6d2-bcc8112c6144 · outbound

This paper cites Forgetting, ignorance or myopia: Revisiting key challenges in online continual learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Forgetting, ignorance or myopia: Revisiting key challenges in online continual learning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:48.918696Z

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.

Observation ba1c913e-9630-4419-a361-c2e84443864f · outbound

This paper cites An em framework for online incremental learning of semantic segmentation.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning An em framework for online incremental learning of semantic segmentation

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:48.700180Z

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.

Observation 5c5a9534-5486-4068-b01f-2582f51e963e · outbound

This paper cites and Zhang, M.-L.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning and Zhang, M.-L

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:48.503228Z

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.

Observation 2c28fa4c-1f83-4a5e-9fcc-cf78f6276df6 · outbound

This paper cites Quaternions and matrices of quaternions.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Quaternions and matrices of quaternions

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:48.342187Z

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.

Observation 1a62493b-902b-4264-a417-222f3c46e999 · outbound

This paper cites and Wu, L.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning and Wu, L

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:48.119191Z

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.

Observation 64f12765-53bc-467b-ab9d-b584dab47f82 · outbound

This paper cites and Zhou, Z.-H.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning and Zhou, Z.-H

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:48.011281Z

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.

Observation 6fa8c2dc-e366-42fe-9183-fefb0ae7efa5 · outbound

This paper cites and Zhou, Z.-H.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning and Zhou, Z.-H

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:47.858903Z

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.

Observation 48fbb0ee-59ee-460e-8f50-6c517dd05316 · outbound

This paper cites Towards class-imbalance aware multi-label learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Towards class-imbalance aware multi-label learning

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:47.672416Z

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.

Observation 000769ed-6e5a-42f8-82b1-e5f85381ec2f · outbound

This paper cites Dynamic Prompt Adjustment for Multi-Label Class-Incremental Learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Dynamic Prompt Adjustment for Multi-Label Class-Incremental Learning

Reference 69

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:14:46.511735Z

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.

Observation ea93175f-ae2b-4aa0-9d35-93ef208c6386 · outbound

This paper cites Deep region and multi-label learning for facial action unit detection.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Deep region and multi-label learning for facial action unit detection

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:47.522633Z

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.

Observation 135a6385-68f8-4def-9106-239ca18c3003 · outbound

This paper cites Image bert pre-training with online tokenizer.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Image bert pre-training with online tokenizer

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:47.361043Z

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.

Observation 8ea54c93-a337-4b24-9e84-936afbc71590 · outbound

This paper cites Prototype augmentation and self-supervision for incremental learning.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning Prototype augmentation and self-supervision for incremental learning

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:14:47.154461Z

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.

Observation 0dd94097-ca92-4eb2-94b9-0714363e3a4e · outbound

This paper cites write newline.

Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning write newline

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T14:14:46.343583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers