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 101–150 of 2644 papers

Title	Date	Tasks	Status	Hype
ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis	Aug 25, 2023	Continual LearningPrognosis	CodeCode Available	1
Continual Action Assessment via Task-Consistent Score-Discriminative Feature Distribution Modeling	Sep 29, 2023	Action AssessmentAction Quality Assessment	CodeCode Available	1
AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?	Oct 28, 2020	Continual LearningOrgan Segmentation	CodeCode Available	1
ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation	Jul 23, 2020	Continual LearningSession-Based Recommendations	CodeCode Available	1
Continual Domain Adaptation through Pruning-aided Domain-specific Weight Modulation	Apr 15, 2023	Continual LearningDomain Adaptation	CodeCode Available	1
Continual evaluation for lifelong learning: Identifying the stability gap	May 26, 2022	Continual LearningIncremental Learning	CodeCode Available	1
Action Flow Matching for Continual Robot Learning	Apr 25, 2025	Continual Learning	CodeCode Available	1
Continual Learning and Private Unlearning	Mar 24, 2022	Continual Learning	CodeCode Available	1
Continual Learning Based on OOD Detection and Task Masking	Mar 17, 2022	class-incremental learningClass Incremental Learning	CodeCode Available	1
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning	Nov 23, 2022	Continual LearningNovel Concepts	CodeCode Available	1
Anytime Continual Learning for Open Vocabulary Classification	Sep 13, 2024	ClassificationContinual Learning	CodeCode Available	1
Continual Learning: Forget-free Winning Subnetworks for Video Representations	Dec 19, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1
Activation-Informed Merging of Large Language Models	Feb 4, 2025	Computational EfficiencyContinual Learning	CodeCode Available	1
Continual Learning for Image Segmentation with Dynamic Query	Nov 29, 2023	Continual LearningDiversity	CodeCode Available	1
Advancing Cross-domain Discriminability in Continual Learning of Vision-Language Models	Jun 27, 2024	Continual LearningIncremental Learning	CodeCode Available	1
Advancing Prompt-Based Methods for Replay-Independent General Continual Learning	Mar 2, 2025	Continual Learning	CodeCode Available	1
Adversarial Continual Learning	Mar 21, 2020	Continual Learningimage-classification	CodeCode Available	1
Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation	Jul 19, 2021	Continual LearningContinual Semantic Segmentation	CodeCode Available	1
Continual Learning from Demonstration of Robotics Skills	Feb 14, 2022	Continual Learning	CodeCode Available	1
Continual Learning in Low-rank Orthogonal Subspaces	Oct 22, 2020	Continual Learning	CodeCode Available	1
Continual Learning in Recurrent Neural Networks	Jun 22, 2020	Continual Learning	CodeCode Available	1
Continual Learning in Task-Oriented Dialogue Systems	Dec 31, 2020	Continual LearningIntent Recognition	CodeCode Available	1
Online Class-Incremental Continual Learning with Adversarial Shapley Value	Aug 31, 2020	Continual LearningOpen-Ended Question Answering	CodeCode Available	1
Continual Learning of Control Primitives: Skill Discovery via Reset-Games	Nov 10, 2020	Continual Learning	CodeCode Available	1
CoDEPS: Online Continual Learning for Depth Estimation and Panoptic Segmentation	Mar 17, 2023	Continual LearningDepth Estimation	CodeCode Available	1
CL-MASR: A Continual Learning Benchmark for Multilingual ASR	Oct 25, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1
A Comprehensive Empirical Evaluation on Online Continual Learning	Aug 20, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1
CLoG: Benchmarking Continual Learning of Image Generation Models	Jun 7, 2024	BenchmarkingContinual Learning	CodeCode Available	1
CLIP model is an Efficient Continual Learner	Oct 6, 2022	Continual LearningIncremental Learning	CodeCode Available	1
CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks	Jun 18, 2022	Continual LearningTransfer Learning	CodeCode Available	1
CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning	May 30, 2025	class-incremental learningClass Incremental Learning	CodeCode Available	1
Class Incremental Learning via Likelihood Ratio Based Task Prediction	Sep 26, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1
Class-Incremental Grouping Network for Continual Audio-Visual Learning	Sep 11, 2023	audio-visual learningclass-incremental learning	CodeCode Available	1
Class-Incremental Learning with Generative Classifiers	Apr 20, 2021	class-incremental learningClass Incremental Learning	CodeCode Available	1
CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models	Mar 28, 2024	Continual Learning	CodeCode Available	1
CLAD: A realistic Continual Learning benchmark for Autonomous Driving	Oct 7, 2022	Autonomous DrivingContinual Learning	CodeCode Available	1
Class-incremental Continual Learning for Instance Segmentation with Image-level Weak Supervision	Jan 1, 2023	Continual LearningIncremental Learning	CodeCode Available	1
CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability	Oct 7, 2021	Continual Learning	CodeCode Available	1
CLR: Channel-wise Lightweight Reprogramming for Continual Learning	Jul 21, 2023	Continual Learningimage-classification	CodeCode Available	1
CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning	Mar 15, 2024	class-incremental learningClass Incremental Learning	CodeCode Available	1
CBA: Improving Online Continual Learning via Continual Bias Adaptor	Aug 14, 2023	Continual Learning	CodeCode Available	1
CaT: Balanced Continual Graph Learning with Graph Condensation	Sep 18, 2023	Continual LearningGraph Learning	CodeCode Available	1
CCL: Continual Contrastive Learning for LiDAR Place Recognition	Mar 24, 2023	Autonomous DrivingContinual Learning	CodeCode Available	1
Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models	Nov 14, 2023	Continual LearningQuestion Answering	CodeCode Available	1
Carousel Memory: Rethinking the Design of Episodic Memory for Continual Learning	Oct 14, 2021	Continual LearningManagement	CodeCode Available	1
Catastrophic Forgetting in Deep Graph Networks: an Introductory Benchmark for Graph Classification	Mar 22, 2021	Continual LearningGeneral Classification	CodeCode Available	1
C-COMA: A CONTINUAL REINFORCEMENT LEARNING MODEL FOR DYNAMIC MULTIAGENT ENVIRONMENTS	Apr 5, 2021	Continual LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Broken Neural Scaling Laws	Oct 26, 2022	Adversarial RobustnessContinual Learning	CodeCode Available	1
Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and Data	Oct 8, 2023	Action RecognitionContinual Learning	CodeCode Available	1
Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning	Mar 16, 2023	Continual Learning	CodeCode Available	1

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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