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 801–850 of 2644 papers

Title	Date	Tasks	Status	Score
IAP: Improving Continual Learning of Vision-Language Models via Instance-Aware Prompting	Mar 26, 2025	class-incremental learningClass Incremental Learning	CodeCode Available	5
Addressing The Devastating Effects Of Single-Task Data Poisoning In Exemplar-Free Continual Learning	Jul 5, 2025	Continual LearningData Poisoning	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
Improving Meta-Continual Learning Representations with Representation Replay	Sep 29, 2021	Continual LearningMeta-Learning	CodeCode Available	5
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification	Feb 19, 2024	ClassificationContinual Learning	CodeCode Available	5
Hierarchically Structured Task-Agnostic Continual Learning	Nov 14, 2022	Continual Learningreinforcement-learning	CodeCode Available	5
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?	Aug 14, 2024	Continual LearningGaussian Processes	CodeCode Available	5
Hierarchically branched diffusion models leverage dataset structure for class-conditional generation	Dec 21, 2022	Continual Learning	CodeCode Available	5
Class-Incremental Learning based on Label Generation	Jun 22, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	5
Continual Segmentation with Disentangled Objectness Learning and Class Recognition	Mar 6, 2024	Continual LearningSegmentation	CodeCode Available	5
Hierarchically Structured Meta-learning	May 13, 2019	ClusteringContinual Learning	CodeCode Available	5
How Do Human Users Teach a Continual Learning Robot in Repeated Interactions?	Jun 30, 2023	Continual 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
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
Continual Stereo Matching of Continuous Driving Scenes With Growing Architecture	Jan 1, 2022	Continual LearningRAG	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
A Natural Gas Consumption Forecasting System for Continual Learning Scenarios based on Hoeffding Trees with Change Point Detection Mechanism	Sep 7, 2023	Change Point DetectionContinual Learning	CodeCode Available	5
Class-Incremental Learning via Knowledge Amalgamation	Sep 5, 2022	class-incremental learningClass Incremental 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 Transformers: Modular Composition and Layer-wise Expansion on a Frozen Substrate	Jul 8, 2025	Continual LearningMixture-of-Experts	CodeCode Available	5
Continual Unsupervised Domain Adaptation for Semantic Segmentation	Oct 19, 2020	Autonomous DrivingContinual Learning	CodeCode Available	5
Continual Learning in Open-vocabulary Classification with Complementary Memory Systems	Jul 4, 2023	Continual Learningimage-classification	CodeCode Available	5
An Attention-based Representation Distillation Baseline for Multi-Label Continual Learning	Jul 19, 2024	Continual LearningTransfer Learning	CodeCode Available	5
Human Inspired Progressive Alignment and Comparative Learning for Grounded Word Acquisition	Jul 5, 2023	Continual LearningLanguage Acquisition	CodeCode Available	5
Continual Learning in Neural Networks	Oct 7, 2019	Continual LearningObject Recognition	CodeCode Available	5
Gradient Episodic Memory for Continual Learning	Jun 26, 2017	Continual LearningIncremental Learning	CodeCode Available	5
Graceful task adaptation with a bi-hemispheric RL agent	Jul 16, 2024	Continual Learning	CodeCode Available	5
Generative vs. Discriminative: Rethinking The Meta-Continual Learning	Dec 1, 2021	Continual LearningMeta-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 Correlation Subspace Learning against Catastrophic Forgetting	Mar 4, 2024	Continual Learning	CodeCode Available	5
Analyzing BERT Cross-lingual Transfer Capabilities in Continual Sequence Labeling	Oct 1, 2022	Continual LearningCross-Lingual Transfer	CodeCode Available	5
Continual Learning In Environments With Polynomial Mixing Times	Dec 13, 2021	Atari GamesContinual Learning	CodeCode Available	5
BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage	Aug 5, 2022	Continual Learning	CodeCode Available	5
Generative Models from the perspective of Continual Learning	Dec 21, 2018	Continual LearningImage Generation	CodeCode Available	5
Multi-task Learning and Catastrophic Forgetting in Continual Reinforcement Learning	Sep 22, 2019	Continual LearningDeep Reinforcement Learning	CodeCode Available	5
Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery	Aug 23, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	5
Growing a Brain with Sparsity-Inducing Generation for Continual Learning	Jan 1, 2023	Action RecognitionContinual Learning	CodeCode Available	5
HINT: Hypernetwork Approach to Training Weight Interval Regions in Continual Learning	May 24, 2024	Continual Learning	CodeCode Available	5
Class-wise Classifier Design Capable of Continual Learning using Adaptive Resonance Theory-based Topological Clustering	Mar 18, 2022	ClassificationClustering	CodeCode Available	5
Integrating Present and Past in Unsupervised Continual Learning	Apr 29, 2024	Continual LearningDiversity	CodeCode Available	5
Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning	Apr 18, 2021	Continual LearningFew-Shot Learning	CodeCode Available	5
From Static to Dynamic: A Continual Learning Framework for Large Language Models	Oct 22, 2023	Continual Learning	CodeCode Available	5
Neural Architecture for Online Ensemble Continual Learning	Nov 27, 2022	Continual Learning	CodeCode Available	5
From Lab to Pocket: A Novel Continual Learning-based Mobile Application for Screening COVID-19	Oct 16, 2024	Continual Learning	CodeCode Available	5
FPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework	Nov 4, 2024	Continual LearningContrastive Learning	CodeCode Available	5
From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning	Mar 16, 2023	BenchmarkingContinual Learning	CodeCode Available	5
Functional Regularisation for Continual Learning with Gaussian Processes	Jan 31, 2019	Bayesian InferenceContinual Learning	CodeCode Available	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	ProgressiveNet	Accuracy	76.16	—	Unverified
2	Piggyback	Accuracy	76.16	—	Unverified
3	CondConvContinual	Accuracy	76.16	—	Unverified
4	CPG	Accuracy	75.81	—	Unverified
5	H$^{2}$	Accuracy	75.71	—	Unverified
6	PackNet	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