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 151–200 of 2644 papers

Title	Date	Tasks	Status	Hype	Score
Continual Learning for Image Segmentation with Dynamic Query	Nov 29, 2023	Continual LearningDiversity	CodeCode Available	1	5
A Multi-Head Model for Continual Learning via Out-of-Distribution Replay	Aug 20, 2022	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
A multifidelity approach to continual learning for physical systems	Apr 8, 2023	Continual Learning	CodeCode Available	1	5
Avalanche RL: a Continual Reinforcement Learning Library	Feb 28, 2022	Continual LearningOpenAI Gym	CodeCode Available	1	5
Batch-level Experience Replay with Review for Continual Learning	Jul 11, 2020	Continual Learning	CodeCode Available	1	5
Bayesian continual learning and forgetting in neural networks	Apr 18, 2025	Bayesian InferenceContinual Learning	CodeCode Available	1	5
Continual Learning For On-Device Environmental Sound Classification	Jul 15, 2022	ClassificationComputational Efficiency	CodeCode Available	1	5
Continual Learning for Segment Anything Model Adaptation	Dec 9, 2024	Continual Learningmodel	CodeCode Available	1	5
Continual Learning for LiDAR Semantic Segmentation: Class-Incremental and Coarse-to-Fine strategies on Sparse Data	Apr 8, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
Model Zoo: A Growing "Brain" That Learns Continually	Jun 6, 2021	Continual LearningLearning Theory	CodeCode Available	1	5
Bilevel Continual Learning	Jul 30, 2020	Bilevel OptimizationContinual Learning	CodeCode Available	1	5
BiasPruner: Debiased Continual Learning for Medical Image Classification	Jul 11, 2024	ClassificationContinual Learning	CodeCode Available	1	5
A unifying framework for generalised Bayesian online learning in non-stationary environments	Nov 15, 2024	Continual LearningMulti-Armed Bandits	CodeCode Available	1	5
Continual Learning in Task-Oriented Dialogue Systems	Dec 31, 2020	Continual LearningIntent Recognition	CodeCode Available	1	5
BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning	May 8, 2023	Continual LearningDiversity	CodeCode Available	1	5
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach	Sep 19, 2022	Bilevel OptimizationContinual Learning	CodeCode Available	1	5
Brain-inspired replay for continual learning with artificial neural networks	Aug 13, 2020	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
Continual Learning for Visual Search with Backward Consistent Feature Embedding	May 26, 2022	Continual Learning	CodeCode Available	1	5
Automating Continual Learning	Dec 1, 2023	Continual Learningimage-classification	CodeCode Available	1	5
Automatic Recall Machines: Internal Replay, Continual Learning and the Brain	Jun 22, 2020	Continual Learning	CodeCode Available	1	5
A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning	Jan 3, 2020	Continual Learningimage-classification	CodeCode Available	1	5
A Comprehensive Empirical Evaluation on Online Continual Learning	Aug 20, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and Data	Oct 8, 2023	Action RecognitionContinual Learning	CodeCode Available	1	5
A Neural Span-Based Continual Named Entity Recognition Model	Feb 23, 2023	Continual LearningContinual Named Entity Recognition	CodeCode Available	1	5
A Comprehensive Survey of Continual Learning: Theory, Method and Application	Jan 31, 2023	Continual LearningLearning Theory	CodeCode Available	1	5
Can LLMs Alleviate Catastrophic Forgetting in Graph Continual Learning? A Systematic Study	May 24, 2025	Continual Learning	CodeCode Available	1	5
Carousel Memory: Rethinking the Design of Episodic Memory for Continual Learning	Oct 14, 2021	Continual LearningManagement	CodeCode Available	1	5
CBA: Improving Online Continual Learning via Continual Bias Adaptor	Aug 14, 2023	Continual Learning	CodeCode Available	1	5
Continual Learning for Abdominal Multi-Organ and Tumor Segmentation	Jun 1, 2023	Continual LearningOrgan Segmentation	CodeCode Available	1	5
CaT: Balanced Continual Graph Learning with Graph Condensation	Sep 18, 2023	Continual LearningGraph Learning	CodeCode Available	1	5
Catastrophic Forgetting in Deep Graph Networks: an Introductory Benchmark for Graph Classification	Mar 22, 2021	Continual LearningGeneral Classification	CodeCode Available	1	5
Continual Learning via Local Module Composition	Nov 15, 2021	Continual LearningTransfer Learning	CodeCode Available	1	5
Continual Learning by Modeling Intra-Class Variation	Oct 11, 2022	Continual Learning	CodeCode Available	1	5
3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding	Dec 13, 2022	Continual LearningIncremental Learning	CodeCode Available	1	5
Anytime Continual Learning for Open Vocabulary Classification	Sep 13, 2024	ClassificationContinual Learning	CodeCode Available	1	5
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning	Aug 18, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning	Mar 16, 2023	Continual Learning	CodeCode Available	1	5
Continual Learning, Fast and Slow	Sep 6, 2022	Continual LearningHippocampus	CodeCode Available	1	5
Continual Learning for Blind Image Quality Assessment	Feb 19, 2021	Continual LearningImage Quality Assessment	CodeCode Available	1	5
A preliminary study on continual learning in computer vision using Kolmogorov-Arnold Networks	Sep 20, 2024	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
A Unified and General Framework for Continual Learning	Mar 20, 2024	Continual Learning	CodeCode Available	1	5
A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm	Oct 18, 2023	Continual LearningIncremental Learning	CodeCode Available	1	5
Compacting, Picking and Growing for Unforgetting Continual Learning	Oct 15, 2019	Age And Gender ClassificationContinual Learning	CodeCode Available	1	5
Continual Multimodal Knowledge Graph Construction	May 15, 2023	Continual Learninggraph construction	CodeCode Available	1	5
Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning	Mar 31, 2024	Continual LearningRepresentation Learning	CodeCode Available	1	5
ARCADe: A Rapid Continual Anomaly Detector	Aug 10, 2020	Anomaly Detectioncontinual anomaly detection	CodeCode Available	1	5
A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials	May 11, 2022	Continual LearningDeepFake Detection	CodeCode Available	1	5
CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models	Mar 28, 2024	Continual Learning	CodeCode Available	1	5
Class-incremental Continual Learning for Instance Segmentation with Image-level Weak Supervision	Jan 1, 2023	Continual LearningIncremental Learning	CodeCode Available	1	5
Continual Learning at the Edge: Real-Time Training on Smartphone Devices	May 24, 2021	Continual Learning	CodeCode Available	1	5

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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