Continual Learning Beyond Experience Rehearsal and Full Model Surrogates | Paper Citation Record

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This paper cites write newline.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates write newline

Reference 1

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This paper cites Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural Activations.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural Activations

Reference 2

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This paper cites Expert gate: Lifelong learning with a network of experts.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Expert gate: Lifelong learning with a network of experts

Reference 3

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This paper cites Online continual learning with maximal interfered retrieval.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Online continual learning with maximal interfered retrieval

Reference 4

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This paper cites Learning fast, learning slow: A general continual learning method based on complementary learning system.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Learning fast, learning slow: A general continual learning method based on complementary learning system

Reference 5

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This paper cites and Laughlin, S.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates and Laughlin, S

Reference 6

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This paper cites SeamlessM4T: Massively Multilingual & Multimodal Machine Translation.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates SeamlessM4T: Massively Multilingual & Multimodal Machine Translation

Reference 7

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Unresolved cited work

Reference 8

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This paper cites Mitigating Interference in the Knowledge Continuum through Attention-Guided Incremental Learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Mitigating Interference in the Knowledge Continuum through Attention-Guided Incremental Learning

Reference 9

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Observation 03efe26d-1afb-438b-8926-2970efc3cae8 · outbound

This paper cites IMEX-Reg: Implicit-Explicit Regularization in the Function Space for Continual Learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates IMEX-Reg: Implicit-Explicit Regularization in the Function Space for Continual Learning

Reference 10

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This paper cites S., Zonooz, B., and Arani, E.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates S., Zonooz, B., and Arani, E

Reference 11

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This paper cites S., Zonooz, B., and Arani, E.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates S., Zonooz, B., and Arani, E

Reference 12

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This paper cites S., Zonooz, B., and Arani, E.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates S., Zonooz, B., and Arani, E

Reference 13

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Observation c6aa77f1-ad63-4b88-8e6e-27c72fa8d1cb · outbound

This paper cites On the effectiveness of lipschitz-driven rehearsal in continual learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates On the effectiveness of lipschitz-driven rehearsal in continual learning

Reference 14

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This paper cites Language Models are Few-Shot Learners.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Language Models are Few-Shot Learners

Reference 15

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This paper cites Dark experience for general continual learning: a strong, simple baseline.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Dark experience for general continual learning: a strong, simple baseline

Reference 16

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

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates New insights on reducing abrupt representation change in online continual learning

Reference 17

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This paper cites New Insights on Reducing Abrupt Representation Change in Online Continual Learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates New Insights on Reducing Abrupt Representation Change in Online Continual Learning

Reference 18

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This paper cites Co2l: Contrastive continual learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Co2l: Contrastive continual learning

Reference 19

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This paper cites K., Ajanthan, T., and Torr, P.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates K., Ajanthan, T., and Torr, P

Reference 20

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This paper cites Xception: Deep Learning with Depthwise Separable Convolutions.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Xception: Deep Learning with Depthwise Separable Convolutions

Reference 21

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This paper cites A continual learning survey: Defying forgetting in classification tasks.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates A continual learning survey: Defying forgetting in classification tasks

Reference 22

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

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 23

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This paper cites Uncertainty-guided continual learning with bayesian neural networks.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Uncertainty-guided continual learning with bayesian neural networks

Reference 24

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This paper cites Continual Learning via Neural Pruning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Continual Learning via Neural Pruning

Reference 25

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This paper cites Fecam: Exploiting the heterogeneity of class distributions in exemplar-free continual learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Fecam: Exploiting the heterogeneity of class distributions in exemplar-free continual learning

Reference 26

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This paper cites Resurrecting old classes with new data for exemplar-free continual learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Resurrecting old classes with new data for exemplar-free continual learning

Reference 27

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This paper cites Network decoupling: From regular to depthwise separable convolutions.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Network decoupling: From regular to depthwise separable convolutions

Reference 28

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This paper cites Depthwise Convolution is All You Need for Learning Multiple Visual Domains.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Depthwise Convolution is All You Need for Learning Multiple Visual Domains

Reference 29

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Unresolved cited work

Reference 30

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This paper cites A., and Pascanu, R.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates A., and Pascanu, R

Reference 31

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This paper cites Deep residual learning for image recognition.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Deep residual learning for image recognition

Reference 32

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This paper cites Pyramidal cell communication within local networks in layer 2/3 of rat neocortex.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Pyramidal cell communication within local networks in layer 2/3 of rat neocortex

Reference 33

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates C., Wang, Z., and Lin, D

Reference 34

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Parameter-efficient transfer learning for nlp

Reference 35

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Inverted residuals and linear bottlenecks: Mobile networks for classification, detection and segmentation

Reference 36

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 37

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates LoRA: Low-Rank Adaptation of Large Language Models

Reference 38

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Compacting, picking and growing for unforgetting continual learning

Reference 39

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates C., Lee, J.-H., Wan, T

Reference 40

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Birt: bio-inspired replay in vision transformers for continual learning

Reference 41

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Unresolved cited work

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Segment Anything

Reference 43

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates A., Milan, K., Quan, J., Ramalho, T., Grabska-Barwinska, A., et al

Reference 44

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Learning multiple layers of features from tiny images

Reference 45

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Unresolved cited work

Reference 46

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates P., Chakravarthi Raja, S., Cheney, N., Clune, J., et al

Reference 47

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Investigating multilingual nmt representations at scale

Reference 48

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates and Yang, X

Reference 49

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Learning from students: Online contrastive distillation network for general continual learning

Reference 50

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates and Hoiem, D

Reference 51

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates and Li, W.-J

Reference 52

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Self-improving reactive agents based on reinforcement learning, planning and teaching

Reference 53

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 54

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This paper cites More classifiers, less forgetting: A generic multi-classifier paradigm for incremental learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates More classifiers, less forgetting: A generic multi-classifier paradigm for incremental learning

Reference 55

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

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Supervised contrastive replay: Revisiting the nearest class mean classifier in online class-incremental continual learning

Reference 56

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates and Lazebnik, S

Reference 57

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Continual Learning Beyond Experience Rehearsal and Full Model Surrogates W., Abdellah, M., Sanchez, C

Reference 58

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Observation 391b6c6a-7871-4554-833a-47efe1aa8f90 · outbound

This paper cites D., and Van De Weijer, J.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates D., and Van De Weijer, J

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:52.615921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a5f1ee6a-b163-417c-b7f0-110f3a96a44e · outbound

This paper cites L., McNaughton, B.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates L., McNaughton, B

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:52.540904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c0eaeb4a-86f9-41ee-8b79-ec7e64ee00c1 · outbound

This paper cites and Cohen, N.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates and Cohen, N

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:43.733642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ddd2d42-0a16-433b-9ac8-d888c2550ea4 · outbound

This paper cites The stability-plasticity dilemma: Investigating the continuum from catastrophic forgetting to age-limited learning effects.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates The stability-plasticity dilemma: Investigating the continuum from catastrophic forgetting to age-limited learning effects

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:43.865396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8e7b678-542c-4f90-93a5-6ed472bc61e8 · outbound

This paper cites I., Chaudhry, A., Yin, D., Hu, H., Pascanu, R., Gorur, D., and Farajtabar, M.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates I., Chaudhry, A., Yin, D., Hu, H., Pascanu, R., Gorur, D., and Farajtabar, M

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:52.426207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b363b435-95c0-4dbb-8e00-80104dd9cdf2 · outbound

This paper cites Can you trust your model's uncertainty? evaluating predictive uncertainty under dataset shift.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Can you trust your model's uncertainty? evaluating predictive uncertainty under dataset shift

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:44.064262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c429746-be49-474a-8ad7-4a5400853b85 · outbound

This paper cites I., Kemker, R., Part, J.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates I., Kemker, R., Part, J

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:44.179208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8db2d0bb-16ed-46b4-9498-6c778fd5221b · outbound

This paper cites an unresolved cited work.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:26:52.302005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7195dc59-2627-4fc5-ae90-4c3d3897b7e5 · outbound

This paper cites Fetril: Feature translation for exemplar-free class-incremental learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Fetril: Feature translation for exemplar-free class-incremental learning

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:52.192644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fe30b154-f1e9-4f82-805a-1a978d19587b · outbound

This paper cites Dualnet: Continual learning, fast and slow.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Dualnet: Continual learning, fast and slow

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:52.103538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fa60db0e-eb03-4346-a341-357166ff2c2e · outbound

This paper cites Continual normalization: Rethinking batch normalization for online continual learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Continual normalization: Rethinking batch normalization for online continual learning

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:51.971878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6745cb12-2097-48b9-83be-9126d784834b · outbound

This paper cites Connectionist models of recognition memory: constraints imposed by learning and forgetting functions.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Connectionist models of recognition memory: constraints imposed by learning and forgetting functions

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:51.712746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fbbbc1db-feba-4da1-9ce3-c7b6d2c2706d · outbound

This paper cites Online structured laplace approximations for overcoming catastrophic forgetting.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Online structured laplace approximations for overcoming catastrophic forgetting

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:51.552715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ea365bd2-c7aa-405b-9227-badbe0543df2 · outbound

This paper cites Progressive Neural Networks.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Progressive Neural Networks

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:44.888043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c356b2fc-de1b-4f2a-8785-c3f1b68cf541 · outbound

This paper cites Gradient Projection Memory for Continual Learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Gradient Projection Memory for Continual Learning

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:44.995114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a51bbaf6-254a-4347-a686-b1bf11014039 · outbound

This paper cites MobileNetV2: Inverted Residuals and Linear Bottlenecks.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates MobileNetV2: Inverted Residuals and Linear Bottlenecks

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:45.112199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40238de3-decc-4593-8db3-6be116af83c5 · outbound

This paper cites Synergy between synaptic consolidation and experience replay for general continual learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Synergy between synaptic consolidation and experience replay for general continual learning

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:51.357338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation efed47ee-cc55-4d25-b8b2-bdb79326166e · outbound

This paper cites Sparse Coding in a Dual Memory System for Lifelong Learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Sparse Coding in a Dual Memory System for Lifelong Learning

Reference 76

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:26:48.321877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5fb61fe4-958a-4243-910f-2ca6c267822f · outbound

This paper cites and Ye, M.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates and Ye, M

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:51.245880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3cf2989d-3410-4247-b235-c647ebf01189 · outbound

This paper cites Rigid-Motion Scattering for Texture Classification.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Rigid-Motion Scattering for Texture Classification

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:45.446733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26c249ff-4076-4d7f-a980-9ed0c53f8f39 · outbound

This paper cites S., Karlinsky, L., Gutta, V., Cascante-Bonilla, P., Kim, D., Arbelle, A., Panda, R., Feris, R., and Kira, Z.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates S., Karlinsky, L., Gutta, V., Cascante-Bonilla, P., Kim, D., Arbelle, A., Panda, R., Feris, R., and Kira, Z

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:45.522461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3599bdc-1459-40db-8f7f-0c295124970d · outbound

This paper cites Decoupling learning and remembering: A bilevel memory framework with knowledge projection for task-incremental learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Decoupling learning and remembering: A bilevel memory framework with knowledge projection for task-incremental learning

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:51.074122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation aa8631d2-aef5-4b24-9d6d-0c4b8fca2316 · outbound

This paper cites Going Deeper With Convolutions.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Going Deeper With Convolutions

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:50.934597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e83cac7a-375e-40bb-ab75-4b12a7edaca3 · outbound

This paper cites Gcr: Gradient coreset based replay buffer selection for continual learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Gcr: Gradient coreset based replay buffer selection for continual learning

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:50.827198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 10c52159-82fe-4923-9b2e-c7960eb62e1c · outbound

This paper cites TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion

Reference 83

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:26:48.036460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3ce476bf-331d-4483-98d5-c0e46d9248c5 · outbound

This paper cites A Comprehensive Survey of Continual Learning: Theory, Method and Application.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates A Comprehensive Survey of Continual Learning: Theory, Method and Application

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:45.961443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9bf39cf-3110-46bd-9036-8202239da17d · outbound

This paper cites S-prompts learning with pre-trained transformers: An occam’s razor for domain incremental learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates S-prompts learning with pre-trained transformers: An occam’s razor for domain incremental learning

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:46.059336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc8898a7-942b-4092-b23f-9f838ac89ffd · outbound

This paper cites Sparcl: Sparse continual learning on the edge.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Sparcl: Sparse continual learning on the edge

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:50.685070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8860d162-9fa2-422e-8f6a-c5cad4b504a3 · outbound

This paper cites Dualprompt: Complementary prompting for rehearsal-free continual learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Dualprompt: Complementary prompting for rehearsal-free continual learning

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:50.634927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d11f0913-7c2f-4a75-8094-d9bb47a45bbe · outbound

This paper cites Learning to prompt for continual learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Learning to prompt for continual learning

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:50.560860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c458de70-2597-487e-9c80-5f0eb2e159af · outbound

This paper cites Large scale incremental learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Large scale incremental learning

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:50.461035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8fce7c73-173b-4d13-bcbe-e44c24d231b6 · outbound

This paper cites an unresolved cited work.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Unresolved cited work

Reference 90

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:26:50.380173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a6212eb3-a10b-4c98-aded-82a0392901d6 · outbound

This paper cites Semantic drift compensation for class-incremental learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Semantic drift compensation for class-incremental learning

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:46.593562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a532a729-909b-4fa6-9f7b-7c43ce4dcabf · outbound

This paper cites B., Ravfogel, S., and Goldberg, Y.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates B., Ravfogel, S., and Goldberg, Y

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:46.665663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fbe6535-ccb9-4ff9-a0a1-b6f10fd9b0d2 · outbound

This paper cites Continual learning through synaptic intelligence.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Continual learning through synaptic intelligence

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:50.306457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b6b68e0d-761b-45e0-b358-327780ff2a9f · outbound

This paper cites Fine-grained knowledge selection and restoration for non-exemplar class incremental learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Fine-grained knowledge selection and restoration for non-exemplar class incremental learning

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:50.233457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 495703ac-7d18-4461-8ef0-08324f0eaf6f · outbound

This paper cites Maintaining discrimination and fairness in class incremental learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Maintaining discrimination and fairness in class incremental learning

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:50.156235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6b7fea03-5566-459e-bedc-7beadaa0f58c · outbound

This paper cites Expandable subspace ensemble for pre-trained model-based class-incremental learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Expandable subspace ensemble for pre-trained model-based class-incremental learning

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:50.062275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation de21e8e0-135d-4c01-96af-1e364c126a10 · outbound

This paper cites Class-incremental learning via dual augmentation.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Class-incremental learning via dual augmentation

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:49.954797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2d21ff69-2036-4eee-801d-cbc9fa2c8f62 · outbound

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

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Prototype augmentation and self-supervision for incremental learning

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:49.869526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 61970400-ee3a-4b71-8481-55c4dc7b8a55 · outbound

This paper cites Self-sustaining representation expansion for non-exemplar class-incremental learning.

Continual Learning Beyond Experience Rehearsal and Full Model Surrogates Self-sustaining representation expansion for non-exemplar class-incremental learning

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:49.801921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers