C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning | Paper Citation Record

Observation 1b8cf154-d507-44df-98c5-5e675ac3c7a3 · outbound

This paper cites Embracing change: Continual learning in deep neural networks,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Embracing change: Continual learning in deep neural networks,

Reference 1

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Observation 83bb9ce9-9bcb-4fce-9e84-35af12d09f85 · outbound

This paper cites Identifying players in broad- cast videos using graph convolutional network,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Identifying players in broad- cast videos using graph convolutional network,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:48.070127Z

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Observation 21248796-f8b1-4851-a4a4-c7f8fb02a2c2 · outbound

This paper cites Class-incremental learning: survey and performance evalua- tion on image classification,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Class-incremental learning: survey and performance evalua- tion on image classification,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:48.056070Z

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Observation 0e6fba71-e5cb-48f6-be32-dee50deaa41f · outbound

This paper cites Class-Incremental Learning: A Survey.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Class-Incremental Learning: A Survey

Reference 4

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Observation 28f25a86-94c7-40c4-b90b-24b76669d46c · outbound

This paper cites Overcoming catastrophic forgetting in incremental object detection via elastic response distillation,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Overcoming catastrophic forgetting in incremental object detection via elastic response distillation,

Reference 5

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Observation 6fe7f66f-04af-4e87-bc10-03d1d9e5c60e · outbound

This paper cites Rlip: Relational language-image pre-training for human-object interaction detection,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Rlip: Relational language-image pre-training for human-object interaction detection,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:48.030072Z

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Observation 64acc9c6-e519-43a7-ad8b-e947fcc60470 · outbound

This paper cites Rlipv2: Fast scaling of relational language-image pre-training,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Rlipv2: Fast scaling of relational language-image pre-training,

Reference 7

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Observation f4e06c96-7b9f-4360-9eee-b89a6ff33606 · outbound

This paper cites PaLM-E: An Embodied Multimodal Language Model.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning PaLM-E: An Embodied Multimodal Language Model

Reference 8

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Observation 53ffc4f0-e91e-41b9-9488-948c7070777b · outbound

This paper cites A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models

Reference 9

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Observation 88d0f9c8-ad7b-41c8-9b32-94943404a24a · outbound

This paper cites Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective

Reference 10

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Observation 6e3ee090-1121-44a6-b0cf-9f0cbe96aa8c · outbound

This paper cites Parameter-Efficient Fine-Tuning for Foundation Models.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Parameter-Efficient Fine-Tuning for Foundation Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T16:16:46.514544Z

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Observation afc21eb9-a968-4f7a-a9d8-1b22fb47f935 · outbound

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

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning A continual learning survey: Defying forgetting in classification tasks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:48.005094Z

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Observation 575984f2-4202-4d8a-8bb9-e161df3995e2 · outbound

This paper cites icarl: Incremental classifier and representation learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning icarl: Incremental classifier and representation learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.991365Z

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Observation 0eee526e-fce8-4dc0-97a0-3d044dea6237 · outbound

This paper cites Experience replay for continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Experience replay for continual learning,

Reference 14

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Observation 24d7d5b3-bca5-4dc0-8cec-0c244f7bac7e · outbound

This paper cites Pcr: Proxy-based contrastive replay for online class-incremental continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Pcr: Proxy-based contrastive replay for online class-incremental continual learning,

Reference 15

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Observation 70ca91ec-7f6b-461b-be4c-658253a66ad3 · outbound

This paper cites Birt: Bio-inspired replay in vision transformers for continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Birt: Bio-inspired replay in vision transformers for continual learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.951742Z

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Observation e8efa756-124b-4d11-9021-05746e63ad74 · outbound

This paper cites A model or 603 exemplars: Towards memory-efficient class-incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning A model or 603 exemplars: Towards memory-efficient class-incremental learning,

Reference 17

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Observation c26e9ae4-24a6-4efd-90e4-9b648049010c · outbound

This paper cites Dense network expansion for class incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Dense network expansion for class incremental learning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.925122Z

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Observation 4b2413b0-ffb5-4650-ab5e-038e798e050e · outbound

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

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Self-sustaining representation expansion for non-exemplar class-incremental learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.913155Z

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Observation e10a5018-47e7-42aa-b715-06c56b713787 · outbound

This paper cites DER: dynamically expandable representation for class incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning DER: dynamically expandable representation for class incremental learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.898649Z

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Observation 7478704b-57d0-4d44-aef5-58e8e3fd44ef · outbound

This paper cites Learning without forgetting,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Learning without forgetting,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.884646Z

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Observation ccbfca4c-b967-41c7-9f84-9a09af26efac · outbound

This paper cites Progressive Learning without Forgetting.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Progressive Learning without Forgetting

Reference 22

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Observation d0d12e78-0699-498c-91e9-8210428ea5da · outbound

This paper cites Parameter-Level Soft-Masking for Continual Learning.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Parameter-Level Soft-Masking for Continual Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T16:16:46.572428Z

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Observation 1395273f-8b5b-42ae-9ef0-4ce971cc88a9 · outbound

This paper cites Continual learn- ing via sequential function-space variational inference,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Continual learn- ing via sequential function-space variational inference,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.870944Z

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Observation 957de4e5-83f3-4c10-bcd5-a6458245570d · outbound

This paper cites Warping the space: Weight space rotation for class-incremental few-shot learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Warping the space: Weight space rotation for class-incremental few-shot learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.857758Z

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Observation 77552d82-7968-4de3-bfc4-d58821862457 · outbound

This paper cites Subspace regularizers for few-shot class incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Subspace regularizers for few-shot class incremental learning,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.845175Z

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Observation 9bf5a6cf-5b96-4275-8efd-58f3d4d47c04 · outbound

This paper cites Continual learning with recursive gradient optimiza- tion,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Continual learning with recursive gradient optimiza- tion,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.832863Z

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Observation 509a5680-0fd2-40cc-8d71-c89f41a99eab · outbound

This paper cites Gradient-based editing of memory examples for online task-free continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Gradient-based editing of memory examples for online task-free continual learning,

Reference 28

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Observation ff5e693d-47e7-45a1-83b1-c919d5f59dc4 · outbound

This paper cites Branch, or layer? zeroth-order optimization for continual learning of vision-language models,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Branch, or layer? zeroth-order optimization for continual learning of vision-language models,

Reference 29

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Observation 2810ec57-331a-4431-bafe-138f884021cd · outbound

This paper cites Asymmetric valleys: Beyond sharp and flat local minima,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Asymmetric valleys: Beyond sharp and flat local minima,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.806953Z

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Observation 335b7ca2-f683-4fa7-b404-3f7ccdc5ad16 · outbound

This paper cites Sharpness-Aware Minimization for Efficiently Improving Generalization.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Sharpness-Aware Minimization for Efficiently Improving Generalization

Reference 31

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Observation 9571ee8a-85ca-4f9d-a297-f62f9bf6bb17 · outbound

This paper cites Improving Sharpness-Aware Minimization with Fisher Mask for Better Generalization on Language Models.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Improving Sharpness-Aware Minimization with Fisher Mask for Better Generalization on Language Models

Reference 32

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Observation 6113dda7-19af-4004-b07e-f90d1d3bee89 · outbound

This paper cites Surrogate Gap Minimization Improves Sharpness-Aware Training.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Surrogate Gap Minimization Improves Sharpness-Aware Training

Reference 33

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Observation b0b8e68d-a654-4b2f-b608-b37456543fd0 · outbound

This paper cites On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima

Reference 34

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Observation 969b00f5-eed0-4fec-889a-36b0f8721fac · outbound

This paper cites Shaping the learning landscape in neural networks around wide flat minima,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Shaping the learning landscape in neural networks around wide flat minima,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.794080Z

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Observation 73d92eeb-8d95-43fc-9201-fb867eab83b0 · outbound

This paper cites Towards efficient and scalable sharpness-aware minimization,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Towards efficient and scalable sharpness-aware minimization,

Reference 36

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Observation c7aa9ba8-bdd1-4ad5-a1a3-0f0cf5275a96 · outbound

This paper cites Sharpness-aware training for free,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Sharpness-aware training for free,

Reference 37

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Observation 5af8f66f-0142-45f9-a028-6030c77b8090 · outbound

This paper cites Sharpness-aware minimization for efficiently improving generalization,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Sharpness-aware minimization for efficiently improving generalization,

Reference 38

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Observation 19b70c85-d722-4aaf-bd24-5a7f758fb7fb · outbound

This paper cites Overcoming catastrophic forgetting in incremental few-shot learning by finding flat minima,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Overcoming catastrophic forgetting in incremental few-shot learning by finding flat minima,

Reference 39

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Observation aa874f5e-8498-4dab-bc3a-45af1614bc78 · outbound

This paper cites Overcoming catastrophic forgetting in continual learning by exploring eigenvalues of hessian matrix,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Overcoming catastrophic forgetting in continual learning by exploring eigenvalues of hessian matrix,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.727231Z

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Observation 277996d1-0271-4adc-b642-382bb5b9ae20 · outbound

This paper cites Flattening sharpness for dynamic gradient projection memory benefits continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Flattening sharpness for dynamic gradient projection memory benefits continual learning,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.714097Z

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Observation eba56abf-ea75-47f9-a449-115207f98aaa · outbound

This paper cites Make continual learning stronger via c-flat,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Make continual learning stronger via c-flat,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.701156Z

Source-reported events for the cited work

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Observation 00f07912-6bb1-481c-ab67-eee6b3e2a46a · outbound

This paper cites Continual learning with pre-trained models: A survey,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Continual learning with pre-trained models: A survey,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.685135Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 54ef8c5a-61e6-4809-a4bc-84dac4a49a1a · outbound

This paper cites Regularizing second-order influences for continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Regularizing second-order influences for continual learning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.672237Z

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Observation b4f249d7-6bd5-49fe-b084-6384cd400ca8 · outbound

This paper cites TRGP: Trust Region Gradient Projection for Continual Learning.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning TRGP: Trust Region Gradient Projection for Continual Learning

Reference 45

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Source-reported events for the cited work

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Observation cc00a7e2-6a84-4173-830a-9ad1dc967a09 · outbound

This paper cites Gradient projection memory for continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Gradient projection memory for continual learning,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.661859Z

Source-reported events for the cited work

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Observation c5c408bf-346b-43bf-ae59-32e6a1d4b9ae · outbound

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

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Decoupling learning and remembering: A bilevel memory framework with knowledge projection for task-incremental learning,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.650566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 16a63612-152e-42a3-a8a6-8b82d47bfb73 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Overcoming catastrophic forgetting in neural networks,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.638795Z

Source-reported events for the cited work

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Observation f191fd20-dc25-4d50-a710-faad6cc42f8b · outbound

This paper cites Cpr: classifier- projection regularization for continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Cpr: classifier- projection regularization for continual learning,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.627529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cbe52c20-4dd3-4c66-85c7-3945b0940087 · outbound

This paper cites Task-aware information routing from common representation space in lifelong learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Task-aware information routing from common representation space in lifelong learning,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.615116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6eaf40ee-f6e7-4594-bd8e-22fd43e1f9f3 · outbound

This paper cites R-dfcil: Relation-guided representation learning for data-free class incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning R-dfcil: Relation-guided representation learning for data-free class incremental learning,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.603319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ba0bf221-26f3-481d-b351-711274b4e1c6 · outbound

This paper cites Alife: Adaptive logit regularizer and feature replay for incremental semantic segmentation,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Alife: Adaptive logit regularizer and feature replay for incremental semantic segmentation,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.587489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f4e5ff41-161d-49ae-9bd0-4d4a36369bcf · outbound

This paper cites Revisiting neural networks for continual learning: An architectural perspective,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Revisiting neural networks for continual learning: An architectural perspective,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.573898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4e5f4eea-93ac-4554-b8b3-93037620e409 · outbound

This paper cites Overcoming catas- trophic forgetting with hard attention to the task,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Overcoming catas- trophic forgetting with hard attention to the task,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.555492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3ac1e195-75d8-48e2-9df6-e7cb553eb527 · outbound

This paper cites Adaptive aggregation networks for class- incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Adaptive aggregation networks for class- incremental learning,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.543232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b59688be-e458-4e44-8bae-c50cb6694b6d · outbound

This paper cites Unigrad-fs: Unified gradient projection with flatter sharpness for continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Unigrad-fs: Unified gradient projection with flatter sharpness for continual learning,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.531776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1c90403a-69b2-4717-bb2d-42034a048fff · outbound

This paper cites An empirical investigation of the role of pre-training in lifelong learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning An empirical investigation of the role of pre-training in lifelong learning,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.518802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a4293b0f-8823-45e2-b350-90f610593c69 · outbound

This paper cites ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-05T16:16:47.123555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 31e0a26d-6339-4d51-997b-a89f8b0f1f41 · outbound

This paper cites Efficient Lifelong Learning with A-GEM.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Efficient Lifelong Learning with A-GEM

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T16:16:46.717705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0008437-004e-4dd6-ae30-eaa9b3f7c376 · outbound

This paper cites Gradient episodic memory for continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Gradient episodic memory for continual learning,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.503920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 38a63f39-33b4-471b-b45e-d4eb582727b8 · outbound

This paper cites Orthogonal gradient descent for continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Orthogonal gradient descent for continual learning,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.488619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5d86be7e-cfe7-4613-a314-b97a1e51fcc4 · outbound

This paper cites Gradient vaccine: Investigating and improving multi-task optimization in massively multilingual models,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Gradient vaccine: Investigating and improving multi-task optimization in massively multilingual models,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.475710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation caca7ee0-cdbe-4ad6-a03a-7c6ef7f157c3 · outbound

This paper cites Sharpness-aware gradient guidance for few-shot class-incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Sharpness-aware gradient guidance for few-shot class-incremental learning,

Reference 63

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T16:16:47.090255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4c26b9bd-8765-4432-8a3e-cf38be23eab7 · outbound

This paper cites Data augmented flatness-aware gradient projection for continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Data augmented flatness-aware gradient projection for continual learning,

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-05T16:16:46.738714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b9edc27-d886-4348-a465-e9f6a4d91ec1 · outbound

This paper cites Sharpness and gradient aware minimization for memory-based continual learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Sharpness and gradient aware minimization for memory-based continual learning,

Reference 65

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T16:16:46.943455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 029b8f06-b180-4622-9b86-f7aff79cc77d · outbound

This paper cites Towards understanding sharpness-aware minimization,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Towards understanding sharpness-aware minimization,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.462982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b66c50fa-4ffd-4a65-b188-c068b35d2274 · outbound

This paper cites Memory aware synapses: Learning what (not) to forget,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Memory aware synapses: Learning what (not) to forget,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.451637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bbfdf047-7af5-4eda-a585-188e2153b11e · outbound

This paper cites Pycil: A python toolbox for class-incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Pycil: A python toolbox for class-incremental learning,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.437922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b453ca2d-ce70-49b9-9774-a1af3ed55572 · outbound

This paper cites Podnet: Pooled outputs distillation for small-tasks incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Podnet: Pooled outputs distillation for small-tasks incremental learning,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.425669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e5d579ce-f310-4b54-98d8-e68c72bf425d · outbound

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

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Maintaining discrimination and fairness in class incremental learning,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.412123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 66ac90dd-bb34-451d-b6cb-f256172a9cf6 · outbound

This paper cites Foster: Feature boosting and compression for class-incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Foster: Feature boosting and compression for class-incremental learning,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.399608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 53d2f381-29ce-4601-9e14-d54314a9712d · outbound

This paper cites Three types of incremental learning,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Three types of incremental learning,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.387941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0132fdfd-1eca-426f-a1a4-1ac600bc5be8 · outbound

This paper cites PyHessian: Neural Networks Through the Lens of the Hessian.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning PyHessian: Neural Networks Through the Lens of the Hessian

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-05T16:16:46.777024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0da47d44-118c-4939-af72-192ca31dc987 · outbound

This paper cites A comprehensive survey of continual learning: Theory, method and application,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning A comprehensive survey of continual learning: Theory, method and application,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.375313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2dd9274e-18ce-4576-bf05-15e342676ff5 · outbound

This paper cites Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-05T16:16:46.786926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbd63be6-81b2-4cea-b397-a9b8a0b19c68 · outbound

This paper cites Moment matching for multi-source domain adaptation,.

C-Flat++: Towards a More Efficient and Powerful Framework for Continual Learning Moment matching for multi-source domain adaptation,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:16:47.361867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers