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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 751–800 of 2644 papers

Title	Date	Tasks	Status	Score
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification	Feb 19, 2024	ClassificationContinual Learning	CodeCode Available	5
Learning to Predict Gradients for Semi-Supervised Continual Learning	Jan 23, 2022	Continual Learning	CodeCode Available	5
Semi-Discriminative Representation Loss for Online Continual Learning	Jun 19, 2020	Continual LearningDiversity	CodeCode Available	5
Continual Learning on Noisy Data Streams via Self-Purified Replay	Oct 14, 2021	Continual LearningSelf-Supervised Learning	CodeCode Available	5
IMEX-Reg: Implicit-Explicit Regularization in the Function Space for Continual Learning	Apr 28, 2024	Continual LearningRepresentation Learning	CodeCode Available	5
IBCL: Zero-shot Model Generation for Task Trade-offs in Continual Learning	Oct 4, 2023	Continual Learningimage-classification	CodeCode Available	5
A Parameter-free Adaptive Resonance Theory-based Topological Clustering Algorithm Capable of Continual Learning	May 1, 2023	ClusteringContinual Learning	CodeCode Available	5
ICICLE: Interpretable Class Incremental Continual Learning	Mar 14, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	5
Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation	Apr 19, 2024	Continual Learning	CodeCode Available	5
Continual Learning on a Data Diet	Oct 23, 2024	Continual Learning	CodeCode Available	5
LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning	Oct 1, 2024	Continual Learning	CodeCode Available	5
HyperMask: Adaptive Hypernetwork-based Masks for Continual Learning	Sep 29, 2023	Continual Learning	CodeCode Available	5
Tuned Compositional Feature Replays for Efficient Stream Learning	Apr 6, 2021	Continual LearningImage Classification	CodeCode Available	5
Continual Learning of Unsupervised Monocular Depth from Videos	Nov 4, 2023	Autonomous DrivingContinual Learning	CodeCode Available	5
Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations	Oct 17, 2018	Continual LearningLanguage Modeling	CodeCode Available	5
Human Inspired Progressive Alignment and Comparative Learning for Grounded Word Acquisition	Jul 5, 2023	Continual LearningLanguage Acquisition	CodeCode Available	5
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?	Aug 14, 2024	Continual LearningGaussian Processes	CodeCode Available	5
How Do Human Users Teach a Continual Learning Robot in Repeated Interactions?	Jun 30, 2023	Continual Learning	CodeCode Available	5
HINT: Hypernetwork Approach to Training Weight Interval Regions in Continual Learning	May 24, 2024	Continual Learning	CodeCode Available	5
IAP: Improving Continual Learning of Vision-Language Models via Instance-Aware Prompting	Mar 26, 2025	class-incremental learningClass Incremental Learning	CodeCode Available	5
Helpful or Harmful: Inter-Task Association in Continual Learning	Oct 23, 2022	Class Incremental LearningContinual Learning	CodeCode Available	5
Hessian Aware Low-Rank Perturbation for Order-Robust Continual Learning	Nov 26, 2023	Continual Learning	CodeCode Available	5
Hierarchically branched diffusion models leverage dataset structure for class-conditional generation	Dec 21, 2022	Continual Learning	CodeCode Available	5
Continual Learning with Weight Interpolation	Apr 5, 2024	Continual Learning	CodeCode Available	5
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts	Jul 9, 2025	Continual LearningIncremental Learning	CodeCode Available	5
Continual Learning of Neural Machine Translation within Low Forgetting Risk Regions	Nov 3, 2022	Continual LearningDomain Adaptation	CodeCode Available	5
Learn the Time to Learn: Replay Scheduling in Continual Learning	Sep 18, 2022	Continual LearningScheduling	CodeCode Available	5
Leveraging Hamilton-Jacobi PDEs with time-dependent Hamiltonians for continual scientific machine learning	Nov 13, 2023	Computational EfficiencyContinual Learning	CodeCode Available	5
A Combinatorial Perspective on Transfer Learning	Oct 23, 2020	Continual LearningTransfer Learning	CodeCode Available	5
Continual Learning of Multi-modal Dynamics with External Memory	Mar 2, 2022	Continual Learning	CodeCode Available	5
Continual Learning of Long Topic Sequences in Neural Information Retrieval	Jan 10, 2022	Continual LearningInformation Retrieval	CodeCode Available	5
Continual Multi-task Gaussian Processes	Oct 31, 2019	Bayesian InferenceContinual Learning	CodeCode Available	5
An Empirical Analysis of Forgetting in Pre-trained Models with Incremental Low-Rank Updates	May 28, 2024	Continual Learning	CodeCode Available	5
Hierarchically Structured Meta-learning	May 13, 2019	ClusteringContinual Learning	CodeCode Available	5
H2ST: Hierarchical Two-Sample Tests for Continual Out-of-Distribution Detection	Jan 1, 2025	Continual LearningIncremental Learning	CodeCode Available	5
Growing a Brain with Sparsity-Inducing Generation for Continual Learning	Jan 1, 2023	Action RecognitionContinual Learning	CodeCode Available	5
Continual Learning of Dynamical Systems with Competitive Federated Reservoir Computing	Jun 27, 2022	Continual Learning	CodeCode Available	5
Growing Transformers: Modular Composition and Layer-wise Expansion on a Frozen Substrate	Jul 8, 2025	Continual LearningMixture-of-Experts	CodeCode Available	5
AdaCL:Adaptive Continual Learning	Mar 23, 2023	Bayesian Optimizationclass-incremental learning	CodeCode Available	5
HAT-CL: A Hard-Attention-to-the-Task PyTorch Library for Continual Learning	Jul 18, 2023	Continual LearningHard Attention	CodeCode Available	5
Hierarchically Structured Task-Agnostic Continual Learning	Nov 14, 2022	Continual Learningreinforcement-learning	CodeCode Available	5
Gradient Correlation Subspace Learning against Catastrophic Forgetting	Mar 4, 2024	Continual Learning	CodeCode Available	5
Graceful task adaptation with a bi-hemispheric RL agent	Jul 16, 2024	Continual Learning	CodeCode Available	5
Approximate Bayesian Class-Conditional Models under Continuous Representation Shift	May 30, 2023	Continual Learning	CodeCode Available	5
Gradient-based Maximally Interfered Retrieval for Domain Incremental 3D Object Detection	Apr 27, 2023	3D Object DetectionAll	CodeCode Available	5
Gradient Episodic Memory for Continual Learning	Jun 26, 2017	Continual LearningIncremental Learning	CodeCode Available	5
Continual Learning: Less Forgetting, More OOD Generalization via Adaptive Contrastive Replay	Oct 9, 2024	Continual LearningContrastive Learning	CodeCode Available	5
BooVAE: Boosting Approach for Continual Learning of VAE	Aug 30, 2019	Continual LearningDiversity	CodeCode Available	5
Continual Learning in the Teacher-Student Setup: Impact of Task Similarity	Jul 9, 2021	Continual Learning	CodeCode Available	5
Generative Models from the perspective of Continual Learning	Dec 21, 2018	Continual LearningImage Generation	CodeCode Available	5

Show:10 25 50

← PrevPage 16 of 53Next →

All datasets ASC (19 tasks)visual domain decathlon (10 tasks)Cifar100 (20 tasks)Tiny-ImageNet (10tasks)F-CelebA (10 tasks)20Newsgroup (10 tasks)CUBS (Fine-grained 6 Tasks)DSC (10 tasks)Flowers (Fine-grained 6 Tasks)ImageNet (Fine-grained 6 Tasks)Sketch (Fine-grained 6 Tasks)Stanford Cars (Fine-grained 6 Tasks)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Multi-task Learning (MTL; Upper Bound)	F1 - macro	0.88	—	Unverified
2	CTR	F1 - macro	0.84	—	Unverified
3	B-CL	F1 - macro	0.81	—	Unverified
4	LAMOL	F1 - macro	0.81	—	Unverified
5	OWM	F1 - macro	0.79	—	Unverified
6	A-GEM	F1 - macro	0.78	—	Unverified
7	HAT	F1 - macro	0.78	—	Unverified
8	Independent Learning (ONE)	F1 - macro	0.78	—	Unverified
9	KAN	F1 - macro	0.77	—	Unverified
10	Naive Continual Learning (NCL)	F1 - macro	0.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	NetTailor	decathlon discipline (Score)	3,744	—	Unverified
2	Depthwise Soft Sharing	decathlon discipline (Score)	3,507	—	Unverified
3	Parallel Res. adapt.	decathlon discipline (Score)	3,412	—	Unverified
4	Depthwise Sharing	decathlon discipline (Score)	3,234	—	Unverified
5	Series Res. adapt.	decathlon discipline (Score)	3,159	—	Unverified
6	Res. adapt. (large)	decathlon discipline (Score)	3,131	—	Unverified
7	DAN	decathlon discipline (Score)	2,851	—	Unverified
8	Piggyback	decathlon discipline (Score)	2,838	—	Unverified
9	Res. adapt. finetune all	decathlon discipline (Score)	2,643	—	Unverified
10	Res. adapt. decay	decathlon discipline (Score)	2,621	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Model Zoo-Continual	Average Accuracy	94.99	—	Unverified
2	ALTA	Average Accuracy	92.98	—	Unverified
3	kNN-CLIP	Average Accuracy	90.8	—	Unverified
4	RMN	Average Accuracy	81	—	Unverified
5	CPG	Average Accuracy	80.9	—	Unverified
6	CondConvContinual	Average Accuracy	77.4	—	Unverified
7	PAENet	Average Accuracy	77.1	—	Unverified
8	CPG-light	Average Accuracy	77	—	Unverified
9	PackNet	Average Accuracy	67.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ALTA-ViTB/16	Average Accuracy	89.8	—	Unverified
2	ALTA-RN50x4	Average Accuracy	84.73	—	Unverified
3	ALTA-RN101	Average Accuracy	83.35	—	Unverified
4	ALTA-RN50	Average Accuracy	81.07	—	Unverified
5	SNCL	Average Accuracy	52.85	—	Unverified
6	DER [buzzega2020dark]	Average Accuracy	51.78	—	Unverified
7	ER[riemer2018learning]	Average Accuracy	48.64	—	Unverified
8	iCaRL [rebuffi2017icarl]	Average Accuracy	31.55	—	Unverified
9	A-GEM [chaudhry2018efficient]	Average Accuracy	25.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CAT (CNN backbone)	Acc	0.76	—	Unverified
2	CAT (MLP backbone)	Acc	0.69	—	Unverified
3	EWC	Acc	0.65	—	Unverified
4	HyperNet	Acc	0.6	—	Unverified
5	PathNet	Acc	0.58	—	Unverified
6	HAT	Acc	0.57	—	Unverified
7	RPSNet	Acc	0.55	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CTR	F1 - macro	0.95	—	Unverified
2	HAT	F1 - macro	0.95	—	Unverified
3	CAT	F1 - macro	0.95	—	Unverified
4	B-CL	F1 - macro	0.95	—	Unverified
5	EWC	F1 - macro	0.92	—	Unverified
6	LAMOL	F1 - macro	0.46	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CondConvContinual	Accuracy	84.26	—	Unverified
2	H$^{2}$	Accuracy	84.1	—	Unverified
3	CPG	Accuracy	83.59	—	Unverified
4	Piggyback	Accuracy	80.5	—	Unverified
5	PackNet	Accuracy	80.41	—	Unverified
6	ProgressiveNet	Accuracy	78.94	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CTR	F1 - macro	0.89	—	Unverified
2	CAT	F1 - macro	0.87	—	Unverified
3	HAT	F1 - macro	0.86	—	Unverified
4	KAN	F1 - macro	0.81	—	Unverified
5	B-CL	F1 - macro	0.77	—	Unverified
6	EWC	F1 - macro	0.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CondConvContinual	Accuracy	97.16	—	Unverified
2	CPG	Accuracy	96.62	—	Unverified
3	H$^{2}$	Accuracy	94.9	—	Unverified
4	Piggyback	Accuracy	94.77	—	Unverified
5	ProgressiveNet	Accuracy	93.41	—	Unverified
6	PackNet	Accuracy	93.04	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Piggyback	Accuracy	76.16	—	Unverified
2	ProgressiveNet	Accuracy	76.16	—	Unverified
3	CondConvContinual	Accuracy	76.16	—	Unverified
4	CPG	Accuracy	75.81	—	Unverified
5	PackNet	Accuracy	75.71	—	Unverified
6	H$^{2}$	Accuracy	75.71	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CondConvContinual	Accuracy	80.77	—	Unverified
2	CPG	Accuracy	80.33	—	Unverified
3	Piggyback	Accuracy	79.91	—	Unverified
4	ProgressiveNet	Accuracy	76.35	—	Unverified
5	H$^{2}$	Accuracy	76.2	—	Unverified
6	PackNet	Accuracy	76.17	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CPG	Accuracy	92.8	—	Unverified
2	CondConvContinual	Accuracy	92.61	—	Unverified
3	H$^{2}$	Accuracy	90.6	—	Unverified
4	Piggyback	Accuracy	89.62	—	Unverified
5	ProgressiveNet	Accuracy	89.21	—	Unverified
6	PackNet	Accuracy	86.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CondConvContinual	Accuracy	78.32	—	Unverified
2	CPG	Accuracy	77.15	—	Unverified
3	H$^{2}$	Accuracy	75.1	—	Unverified
4	ProgressiveNet	Accuracy	74.94	—	Unverified
5	Piggyback	Accuracy	71.33	—	Unverified
6	PackNet	Accuracy	69.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ALTA-ViTB/16	Average Accuracy	92.85	—	Unverified
2	ALTA-RN50x4	Average Accuracy	84.91	—	Unverified
3	RMN (Resnet)	Average Accuracy	84.9	—	Unverified
4	ALTA-RN101	Average Accuracy	84.77	—	Unverified
5	ALTA-RN50	Average Accuracy	83.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RMN	Accuracy	68.1	—	Unverified
2	CondConvContinual	Accuracy	61.32	—	Unverified
3	CCGN	Accuracy	35.24	—	Unverified
4	DGMw	Accuracy	17.82	—	Unverified
5	DGMa	Accuracy	15.16	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RMN	Average Accuracy	97.99	—	Unverified
2	Model Zoo-Continual	Average Accuracy	97.71	—	Unverified
3	CODE-CL	Average Accuracy	96.56	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TAG-RMSProp	Accuracy	62.59	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CODE-CL	Average Accuracy	93.32	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TEST	1:3 Accuracy	2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TAG-RMSProp	Average Accuracy	62.79	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IBM	Accuracy	82.69	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IBM	Accuracy	88.15	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Model Zoo-Continual	Average Accuracy	84.27	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TAG-RMSProp	Accuracy	61.58	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CODE-CL	Average Accuracy	68.83	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TAG-RMSProp	Accuracy	57.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IBM	Accuracy	53.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MRM	Acc	78.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Model Zoo-Continual	Average Accuracy	99.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CODE-CL	Average Accuracy	77.21	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	H$^{2}$	Top 1 Accuracy %	97.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	H$^{2}$	Top 1 Accuracy %	99.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IBM	Accuracy	52.38	—	Unverified