SOTAVerified

Continual Learning

Continual Learning (also known as Incremental Learning, Life-long Learning) is a concept to learn a model for a large number of tasks sequentially without forgetting knowledge obtained from the preceding tasks, where the data in the old tasks are not available anymore during training new ones.
If not mentioned, the benchmarks here are Task-CL, where task-id is provided on validation.

Source:
Continual Learning by Asymmetric Loss Approximation with Single-Side Overestimation
Three scenarios for continual learning
Lifelong Machine Learning
Continual lifelong learning with neural networks: A review

Papers

Showing 21012150 of 2644 papers

TitleStatusHype
Growing Representation Learning0
Simplest Streaming TreesCode0
Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora0
Continual Learning on Noisy Data Streams via Self-Purified ReplayCode0
FedSpeech: Federated Text-to-Speech with Continual Learning0
Block Contextual MDPs for Continual Learning0
Continual learning using lattice-free MMI for speech recognition0
Continual Learning with Differential PrivacyCode0
Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse NetworksCode0
Cognitively Inspired Learning of Incremental Drifting Concepts0
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning0
Hypernetworks for Continual Semi-Supervised Learning0
GROWN: GRow Only When Necessary for Continual Learning0
Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problemsCode0
Mako: Semi-supervised continual learning with minimal labeled data via data programming0
On the Convergence of Nonconvex Continual Learning with Adaptive Learning Rate0
Pretrained Language Model in Continual Learning: A Comparative Study0
A Unified Knowledge Distillation Framework for Deep Directed Graphical Models0
Chameleon Sampling: Diverse and Pure Example Selection for Online Continual Learning with Noisy Labels0
Optimizing Class Distribution in Memory for Multi-Label Continual Learning0
Continual Learning via Low-Rank Network Updates0
Towards a theory of out-of-distribution learning0
Gradient Imbalance and solution in Online Continual learning0
Designing Less Forgetful Networks for Continual Learning0
Brain insights improve RNNs' accuracy and robustness for hierarchical control of continually learned autonomous motor motifs0
Improving Meta-Continual Learning Representations with Representation ReplayCode0
Continual Learning Using Task Conditional Neural Networks0
Model Zoo: A Growing Brain That Learns Continually0
Continual Learning of Neural Networks for Realtime Wireline Cable Position Inference0
Design and Evaluation for Robust Continual Learning0
ACCTS: an Adaptive Model Training Policy for Continuous Classification of Time Series0
Continual Learning Using Pseudo-Replay via Latent Space Sampling0
Ensembles and Encoders for Task-Free Continual Learning0
Effect of scale on catastrophic forgetting in neural networks0
Closed-loop Control for Online Continual Learning0
Learn the Time to Learn: Replay Scheduling for Continual Learning0
Partially Relaxed Masks for Lightweight Knowledge Transfer without Forgetting in Continual Learning0
Formalizing the Generalization-Forgetting Trade-off in Continual Learning0
Bayesian deep learning of affordances from RGB images0
Lifelong 3D Object Recognition and Grasp Synthesis Using Dual Memory Recurrent Self-Organization NetworksCode0
Recent Advances of Continual Learning in Computer Vision: An Overview0
Towards Generalized and Incremental Few-Shot Object Detection0
Continual Learning with Memory Cascades0
Stabilizing Elastic Weight Consolidation method in practical ML tasks and using weight importances for neural network pruningCode0
Learning offline: memory replay in biological and artificial reinforcement learning0
Unsupervised Continual Learning in Streaming Environments0
Class incremental learning for video action classification0
Evaluating Continual Learning Algorithms by Generating 3D Virtual Environments0
Total Recall: a Customized Continual Learning Method for Neural Semantic ParsersCode0
Saliency Guided Experience Packing for Replay in Continual LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Multi-task Learning (MTL; Upper Bound)F1 - macro0.88Unverified
2CTRF1 - macro0.84Unverified
3B-CLF1 - macro0.81Unverified
4LAMOLF1 - macro0.81Unverified
5OWMF1 - macro0.79Unverified
6A-GEMF1 - macro0.78Unverified
7HATF1 - macro0.78Unverified
8Independent Learning (ONE)F1 - macro0.78Unverified
9KANF1 - macro0.77Unverified
10Naive Continual Learning (NCL)F1 - macro0.77Unverified
#ModelMetricClaimedVerifiedStatus
1NetTailordecathlon discipline (Score)3,744Unverified
2Depthwise Soft Sharingdecathlon discipline (Score)3,507Unverified
3Parallel Res. adapt.decathlon discipline (Score)3,412Unverified
4Depthwise Sharingdecathlon discipline (Score)3,234Unverified
5Series Res. adapt.decathlon discipline (Score)3,159Unverified
6Res. adapt. (large)decathlon discipline (Score)3,131Unverified
7DANdecathlon discipline (Score)2,851Unverified
8Piggybackdecathlon discipline (Score)2,838Unverified
9Res. adapt. finetune alldecathlon discipline (Score)2,643Unverified
10Res. adapt. decaydecathlon discipline (Score)2,621Unverified
#ModelMetricClaimedVerifiedStatus
1Model Zoo-ContinualAverage Accuracy94.99Unverified
2ALTAAverage Accuracy92.98Unverified
3kNN-CLIPAverage Accuracy90.8Unverified
4RMNAverage Accuracy81Unverified
5CPGAverage Accuracy80.9Unverified
6CondConvContinualAverage Accuracy77.4Unverified
7PAENetAverage Accuracy77.1Unverified
8CPG-lightAverage Accuracy77Unverified
9PackNetAverage Accuracy67.5Unverified
#ModelMetricClaimedVerifiedStatus
1ALTA-ViTB/16Average Accuracy89.8Unverified
2ALTA-RN50x4Average Accuracy84.73Unverified
3ALTA-RN101Average Accuracy83.35Unverified
4ALTA-RN50Average Accuracy81.07Unverified
5SNCLAverage Accuracy52.85Unverified
6DER [buzzega2020dark]Average Accuracy51.78Unverified
7ER[riemer2018learning]Average Accuracy48.64Unverified
8iCaRL [rebuffi2017icarl]Average Accuracy31.55Unverified
9A-GEM [chaudhry2018efficient]Average Accuracy25.33Unverified
#ModelMetricClaimedVerifiedStatus
1CAT (CNN backbone)Acc0.76Unverified
2CAT (MLP backbone)Acc0.69Unverified
3EWCAcc0.65Unverified
4HyperNetAcc0.6Unverified
5PathNetAcc0.58Unverified
6HATAcc0.57Unverified
7RPSNetAcc0.55Unverified
#ModelMetricClaimedVerifiedStatus
1CTRF1 - macro0.95Unverified
2HATF1 - macro0.95Unverified
3CATF1 - macro0.95Unverified
4B-CLF1 - macro0.95Unverified
5EWCF1 - macro0.92Unverified
6LAMOLF1 - macro0.46Unverified
#ModelMetricClaimedVerifiedStatus
1CondConvContinualAccuracy84.26Unverified
2H$^{2}$Accuracy84.1Unverified
3CPGAccuracy83.59Unverified
4PiggybackAccuracy80.5Unverified
5PackNetAccuracy80.41Unverified
6ProgressiveNetAccuracy78.94Unverified
#ModelMetricClaimedVerifiedStatus
1CTRF1 - macro0.89Unverified
2CATF1 - macro0.87Unverified
3HATF1 - macro0.86Unverified
4KANF1 - macro0.81Unverified
5B-CLF1 - macro0.77Unverified
6EWCF1 - macro0.66Unverified
#ModelMetricClaimedVerifiedStatus
1CondConvContinualAccuracy97.16Unverified
2CPGAccuracy96.62Unverified
3H$^{2}$Accuracy94.9Unverified
4PiggybackAccuracy94.77Unverified
5ProgressiveNetAccuracy93.41Unverified
6PackNetAccuracy93.04Unverified
#ModelMetricClaimedVerifiedStatus
1PiggybackAccuracy76.16Unverified
2ProgressiveNetAccuracy76.16Unverified
3CondConvContinualAccuracy76.16Unverified
4CPGAccuracy75.81Unverified
5PackNetAccuracy75.71Unverified
6H$^{2}$Accuracy75.71Unverified
#ModelMetricClaimedVerifiedStatus
1CondConvContinualAccuracy80.77Unverified
2CPGAccuracy80.33Unverified
3PiggybackAccuracy79.91Unverified
4ProgressiveNetAccuracy76.35Unverified
5H$^{2}$Accuracy76.2Unverified
6PackNetAccuracy76.17Unverified
#ModelMetricClaimedVerifiedStatus
1CPGAccuracy92.8Unverified
2CondConvContinualAccuracy92.61Unverified
3H$^{2}$Accuracy90.6Unverified
4PiggybackAccuracy89.62Unverified
5ProgressiveNetAccuracy89.21Unverified
6PackNetAccuracy86.11Unverified
#ModelMetricClaimedVerifiedStatus
1CondConvContinualAccuracy78.32Unverified
2CPGAccuracy77.15Unverified
3H$^{2}$Accuracy75.1Unverified
4ProgressiveNetAccuracy74.94Unverified
5PiggybackAccuracy71.33Unverified
6PackNetAccuracy69.4Unverified
#ModelMetricClaimedVerifiedStatus
1ALTA-ViTB/16Average Accuracy92.85Unverified
2ALTA-RN50x4Average Accuracy84.91Unverified
3RMN (Resnet)Average Accuracy84.9Unverified
4ALTA-RN101Average Accuracy84.77Unverified
5ALTA-RN50Average Accuracy83.87Unverified
#ModelMetricClaimedVerifiedStatus
1RMNAccuracy68.1Unverified
2CondConvContinualAccuracy61.32Unverified
3CCGNAccuracy35.24Unverified
4DGMwAccuracy17.82Unverified
5DGMaAccuracy15.16Unverified
#ModelMetricClaimedVerifiedStatus
1RMNAverage Accuracy97.99Unverified
2Model Zoo-ContinualAverage Accuracy97.71Unverified
3CODE-CLAverage Accuracy96.56Unverified
#ModelMetricClaimedVerifiedStatus
1TAG-RMSPropAccuracy62.59Unverified
#ModelMetricClaimedVerifiedStatus
1CODE-CLAverage Accuracy93.32Unverified
#ModelMetricClaimedVerifiedStatus
1TEST1:3 Accuracy2Unverified
#ModelMetricClaimedVerifiedStatus
1TAG-RMSPropAverage Accuracy62.79Unverified
#ModelMetricClaimedVerifiedStatus
1IBMAccuracy82.69Unverified
#ModelMetricClaimedVerifiedStatus
1IBMAccuracy88.15Unverified
#ModelMetricClaimedVerifiedStatus
1Model Zoo-ContinualAverage Accuracy84.27Unverified
#ModelMetricClaimedVerifiedStatus
1TAG-RMSPropAccuracy61.58Unverified
#ModelMetricClaimedVerifiedStatus
1CODE-CLAverage Accuracy68.83Unverified
#ModelMetricClaimedVerifiedStatus
1TAG-RMSPropAccuracy57.2Unverified
#ModelMetricClaimedVerifiedStatus
1IBMAccuracy53.9Unverified
#ModelMetricClaimedVerifiedStatus
1MRMAcc78.4Unverified
#ModelMetricClaimedVerifiedStatus
1Model Zoo-ContinualAverage Accuracy99.66Unverified
#ModelMetricClaimedVerifiedStatus
1CODE-CLAverage Accuracy77.21Unverified
#ModelMetricClaimedVerifiedStatus
1H$^{2}$Top 1 Accuracy %97.3Unverified
#ModelMetricClaimedVerifiedStatus
1H$^{2}$Top 1 Accuracy %99.9Unverified
#ModelMetricClaimedVerifiedStatus
1IBMAccuracy52.38Unverified