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 551–600 of 2644 papers

Title	Date	Tasks	Status	Hype	Score
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation	Oct 12, 2020	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1	5
Interactive incremental learning of generalizable skills with local trajectory modulation	Sep 9, 2024	Continual LearningImitation Learning	CodeCode Available	0	5
Continual adaptation for efficient machine communication	Nov 22, 2019	Continual LearningLanguage Modeling	CodeCode Available	0	5
Continual Active Learning Using Pseudo-Domains for Limited Labelling Resources and Changing Acquisition Characteristics	Nov 25, 2021	Active LearningAge Estimation	CodeCode Available	0	5
Integrating Present and Past in Unsupervised Continual Learning	Apr 29, 2024	Continual LearningDiversity	CodeCode Available	0	5
Introducing Language Guidance in Prompt-based Continual Learning	Aug 30, 2023	Continual Learning	CodeCode Available	0	5
Instance exploitation for learning temporary concepts from sparsely labeled drifting data streams	Sep 20, 2020	Continual Learning	CodeCode Available	0	5
Integrating Curricula with Replays: Its Effects on Continual Learning	Jul 8, 2023	Continual LearningTransfer Learning	CodeCode Available	0	5
Adversarial Training of Variational Auto-encoders for Continual Zero-shot Learning(A-CZSL)	Feb 7, 2021	Continual LearningGeneralized Zero-Shot Learning	CodeCode Available	0	5
ContCap: A scalable framework for continual image captioning	Sep 19, 2019	Continual LearningImage Captioning	CodeCode Available	0	5
Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification	Feb 19, 2024	ClassificationContinual Learning	CodeCode Available	0	5
IRS: Incremental Relationship-guided Segmentation for Digital Pathology	May 28, 2025	Continual LearningDomain Generalization	CodeCode Available	0	5
Incremental Task Learning with Incremental Rank Updates	Jul 19, 2022	Continual Learning	CodeCode Available	0	5
iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning	Jul 12, 2024	class-incremental learningClass Incremental Learning	CodeCode Available	0	5
Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition	Nov 9, 2021	Continual LearningKnowledge Distillation	CodeCode Available	0	5
Consistency is the key to further mitigating catastrophic forgetting in continual learning	Jul 11, 2022	Continual LearningSelf-Supervised Learning	CodeCode Available	0	5
Improving Replay-Based Continual Semantic Segmentation with Smart Data Selection	Sep 20, 2022	Continual LearningContinual Semantic Segmentation	CodeCode Available	0	5
Augmenting Replay in World Models for Continual Reinforcement Learning	Jan 30, 2024	Continual LearningModel-based Reinforcement Learning	CodeCode Available	0	5
Improving Representational Continuity via Continued Pretraining	Feb 26, 2023	Continual LearningRepresentation Learning	CodeCode Available	0	5
Improving Online Continual Learning Performance and Stability with Temporal Ensembles	Jun 29, 2023	Continual Learning	CodeCode Available	0	5
Adversarial Robust Memory-Based Continual Learner	Nov 29, 2023	Adversarial RobustnessContinual Learning	CodeCode Available	0	5
Condensed Composite Memory Continual Learning	Feb 19, 2021	Continual Learning	CodeCode Available	0	5
Adversarially Diversified Rehearsal Memory (ADRM): Mitigating Memory Overfitting Challenge in Continual Learning	May 20, 2024	Continual LearningDiversity	CodeCode Available	0	5
Attentive Federated Learning for Concept Drift in Distributed 5G Edge Networks	Nov 14, 2021	Continual LearningEdge-computing	CodeCode Available	0	5
Improving Forward Compatibility in Class Incremental Learning by Increasing Representation Rank and Feature Richness	Mar 22, 2024	class-incremental learningClass Incremental Learning	CodeCode Available	0	5
Improving Meta-Continual Learning Representations with Representation Replay	Sep 29, 2021	Continual LearningMeta-Learning	CodeCode Available	0	5
In-context Continual Learning Assisted by an External Continual Learner	Dec 20, 2024	Continual LearningIn-Context Learning	CodeCode Available	0	5
IMEX-Reg: Implicit-Explicit Regularization in the Function Space for Continual Learning	Apr 28, 2024	Continual LearningRepresentation Learning	CodeCode Available	0	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	0	5
A Brief Review of Hypernetworks in Deep Learning	Jun 12, 2023	Causal InferenceContinual Learning	CodeCode Available	0	5
IBCL: Zero-shot Model Generation for Task Trade-offs in Continual Learning	Oct 4, 2023	Continual Learningimage-classification	CodeCode Available	0	5
Attend Before you Act: Leveraging human visual attention for continual learning	Jul 25, 2018	Continual LearningDecision Making	CodeCode Available	0	5
Compression-aware Continual Learning using Singular Value Decomposition	Sep 3, 2020	Continual LearningModel Compression	CodeCode Available	0	5
IAP: Improving Continual Learning of Vision-Language Models via Instance-Aware Prompting	Mar 26, 2025	class-incremental learningClass Incremental Learning	CodeCode Available	0	5
ICICLE: Interpretable Class Incremental Continual Learning	Mar 14, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	0	5
Improving Data-aware and Parameter-aware Robustness for Continual Learning	May 27, 2024	Continual Learning	CodeCode Available	0	5
Incorporating brain-inspired mechanisms for multimodal learning in artificial intelligence	May 15, 2025	Computational EfficiencyContinual Learning	CodeCode Available	0	5
Compressed Latent Replays for Lightweight Continual Learning on Spiking Neural Networks	May 8, 2024	Continual Learning	CodeCode Available	0	5
Human Inspired Progressive Alignment and Comparative Learning for Grounded Word Acquisition	Jul 5, 2023	Continual LearningLanguage Acquisition	CodeCode Available	0	5
Complex Facial Expression Recognition Using Deep Knowledge Distillation of Basic Features	Aug 11, 2023	Continual LearningEmotion Recognition	CodeCode Available	0	5
Complementary Calibration: Boosting General Continual Learning with Collaborative Distillation and Self-Supervision	Sep 3, 2021	Continual LearningContrastive Learning	CodeCode Available	0	5
HINT: Hypernetwork Approach to Training Weight Interval Regions in Continual Learning	May 24, 2024	Continual Learning	CodeCode Available	0	5
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?	Aug 14, 2024	Continual LearningGaussian Processes	CodeCode Available	0	5
How Do Human Users Teach a Continual Learning Robot in Repeated Interactions?	Jun 30, 2023	Continual Learning	CodeCode Available	0	5
Hierarchically Structured Meta-learning	May 13, 2019	ClusteringContinual Learning	CodeCode Available	0	5
Hierarchically Structured Task-Agnostic Continual Learning	Nov 14, 2022	Continual Learningreinforcement-learning	CodeCode Available	0	5
HyperMask: Adaptive Hypernetwork-based Masks for Continual Learning	Sep 29, 2023	Continual Learning	CodeCode Available	0	5
ATLAS: Adapter-Based Multi-Modal Continual Learning with a Two-Stage Learning Strategy	Oct 14, 2024	Continual Learning	CodeCode Available	0	5
CoLLIE: Continual Learning of Language Grounding from Language-Image Embeddings	Nov 15, 2021	Continual LearningFew-Shot Learning	CodeCode Available	0	5
Hessian Aware Low-Rank Perturbation for Order-Robust Continual Learning	Nov 26, 2023	Continual Learning	CodeCode Available	0	5

Show:10 25 50

← PrevPage 12 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