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 2601–2644 of 2644 papers

Title	Date	Tasks	Status
Continual Learning of Context-dependent Processing in Neural Networks	Sep 29, 2018	Continual Learning	CodeCode Available
Online Task-Free Continual Learning via Dynamic Expansionable Memory Distribution	Jan 1, 2025	Continual Learning	CodeCode Available
Technical Report for the 5th CLVision Challenge at CVPR: Addressing the Class-Incremental with Repetition using Unlabeled Data -- 4th Place Solution	Mar 19, 2025	class-incremental learningClass Incremental Learning	CodeCode Available
Temporal Continual Learning with Prior Compensation for Human Motion Prediction	Jul 5, 2025	Continual LearningHuman motion prediction	CodeCode Available
Class-wise Classifier Design Capable of Continual Learning using Adaptive Resonance Theory-based Topological Clustering	Mar 18, 2022	ClassificationClustering	CodeCode Available
On Sequential Bayesian Inference for Continual Learning	Jan 4, 2023	Bayesian InferenceContinual Learning	CodeCode Available
On Sequential Loss Approximation for Continual Learning	May 26, 2024	class-incremental learningClass Incremental Learning	CodeCode Available
Continual Unsupervised Domain Adaptation for Semantic Segmentation	Oct 19, 2020	Autonomous DrivingContinual Learning	CodeCode Available
SCStory: Self-supervised and Continual Online Story Discovery	Nov 27, 2023	ArticlesContinual Learning	CodeCode Available
CLASSP: a Biologically-Inspired Approach to Continual Learning through Adjustment Suppression and Sparsity Promotion	Apr 29, 2024	Continual LearningSentiment Analysis	CodeCode Available
On the Design of Safe Continual RL Methods for Control of Nonlinear Systems	Feb 21, 2025	Continual LearningMuJoCo	CodeCode Available
On the Diminishing Returns of Width for Continual Learning	Mar 11, 2024	Continual LearningLearning Theory	CodeCode Available
Temporal-Difference Variational Continual Learning	Oct 10, 2024	Continual Learning	CodeCode Available
Continual Task Learning through Adaptive Policy Self-Composition	Nov 18, 2024	Continual LearningOffline RL	CodeCode Available
SEE: Continual Fine-tuning with Sequential Ensemble of Experts	Apr 9, 2025	Continual LearningMulti-Task Learning	CodeCode Available
On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers	Aug 18, 2023	Continual LearningTransfer Learning	CodeCode Available
Continual Stereo Matching of Continuous Driving Scenes With Growing Architecture	Jan 1, 2022	Continual LearningRAG	CodeCode Available
Continual Segmentation with Disentangled Objectness Learning and Class Recognition	Mar 6, 2024	Continual LearningSegmentation	CodeCode Available
Adapting Diffusion Models for Improved Prompt Compliance and Controllable Image Synthesis	Oct 29, 2024	Continual LearningImage Generation	CodeCode Available
SEEKR: Selective Attention-Guided Knowledge Retention for Continual Learning of Large Language Models	Nov 9, 2024	Continual Learning	CodeCode Available
SegACIL: Solving the Stability-Plasticity Dilemma in Class-Incremental Semantic Segmentation	Dec 14, 2024	Class-Incremental Semantic SegmentationContinual Learning	CodeCode Available
Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?	Oct 27, 2022	Continual LearningLesion Segmentation	CodeCode Available
Class-Incremental Learning with Repetition	Jan 26, 2023	class-incremental learningClass Incremental Learning	CodeCode Available
Class-Incremental Learning via Knowledge Amalgamation	Sep 5, 2022	class-incremental learningClass Incremental Learning	CodeCode Available
Open Continual Feature Selection via Granular-Ball Knowledge Transfer	Mar 15, 2024	Continual Learningfeature selection	CodeCode Available
3D_DEN: Open-ended 3D Object Recognition using Dynamically Expandable Networks	Sep 15, 2020	3D Object RecognitionContinual Learning	CodeCode Available
Continual Representation Learning for Biometric Identification	Jun 8, 2020	Continual LearningKnowledge Distillation	CodeCode Available
ATLAS: Adapter-Based Multi-Modal Continual Learning with a Two-Stage Learning Strategy	Oct 14, 2024	Continual Learning	CodeCode Available
Class-Incremental Learning based on Label Generation	Jun 22, 2023	class-incremental learningClass Incremental Learning	CodeCode Available
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition	May 28, 2019	Audio ClassificationBayesian Inference	CodeCode Available
Selective Attention-based Modulation for Continual Learning	Mar 29, 2024	Continual LearningSaliency Prediction	CodeCode Available
Wasserstein Expansible Variational Autoencoder for Discriminative and Generative Continual Learning	Jan 1, 2023	Continual LearningDiversity	CodeCode Available
Selective Replay Enhances Learning in Online Continual Analogical Reasoning	Mar 6, 2021	Continual Learningimage-classification	CodeCode Available
Class-Incremental Experience Replay for Continual Learning under Concept Drift	Apr 24, 2021	Continual Learningvalid	CodeCode Available
A Theoretical Framework for Inference and Learning in Predictive Coding Networks	Jul 21, 2022	Continual Learning	CodeCode Available
Continual Reinforcement Learning for HVAC Systems Control: Integrating Hypernetworks and Transfer Learning	Mar 24, 2025	Continual LearningDeep Reinforcement Learning	CodeCode Available
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition	Feb 25, 2019	Continual LearningFairness	CodeCode Available
Continual Prune-and-Select: Class-incremental learning with specialized subnetworks	Aug 9, 2022	class-incremental learningClass Incremental Learning	CodeCode Available
Adapt before Continual Learning	Jun 4, 2025	Continual Learning	CodeCode Available
Self-Evolved Dynamic Expansion Model for Task-Free Continual Learning	Jan 1, 2023	Continual LearningDiversity	CodeCode Available
Class Gradient Projection For Continual Learning	Nov 25, 2023	Continual LearningContrastive Learning	CodeCode Available
Approximate Bayesian Class-Conditional Models under Continuous Representation Shift	May 30, 2023	Continual Learning	CodeCode Available
Continual Panoptic Perception: Towards Multi-modal Incremental Interpretation of Remote Sensing Images	Jul 19, 2024	Caption GenerationContinual Learning	CodeCode Available
Self-Net: Lifelong Learning via Continual Self-Modeling	May 25, 2018	Continual LearningLifelong learning	CodeCode Available

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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