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	Score
Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments	Dec 31, 2021	Continual LearningDeep Learning	CodeCode Available	1	5
Continual Learning, Fast and Slow	Sep 6, 2022	Continual LearningHippocampus	CodeCode Available	1	5
AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?	Oct 28, 2020	Continual LearningOrgan Segmentation	CodeCode Available	1	5
ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation	Jul 23, 2020	Continual LearningSession-Based Recommendations	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 Image Segmentation with Dynamic Query	Nov 29, 2023	Continual LearningDiversity	CodeCode Available	1	5
Continual All-in-One Adverse Weather Removal with Knowledge Replay on a Unified Network Structure	Mar 12, 2024	AllContinual Learning	CodeCode Available	1	5
BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning	Nov 26, 2022	Continual Learning	CodeCode Available	1	5
Continual Learning for Segment Anything Model Adaptation	Dec 9, 2024	Continual Learningmodel	CodeCode Available	1	5
Continual BERT: Continual Learning for Adaptive Extractive Summarization of COVID-19 Literature	Jul 7, 2020	Continual LearningExtractive Summarization	CodeCode Available	1	5
BiasPruner: Debiased Continual Learning for Medical Image Classification	Jul 11, 2024	ClassificationContinual Learning	CodeCode Available	1	5
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach	Sep 19, 2022	Bilevel OptimizationContinual Learning	CodeCode Available	1	5
Activation-Informed Merging of Large Language Models	Feb 4, 2025	Computational EfficiencyContinual Learning	CodeCode Available	1	5
Bilevel Continual Learning	Jul 30, 2020	Bilevel OptimizationContinual Learning	CodeCode Available	1	5
Advancing Cross-domain Discriminability in Continual Learning of Vision-Language Models	Jun 27, 2024	Continual LearningIncremental Learning	CodeCode Available	1	5
Advancing Prompt-Based Methods for Replay-Independent General Continual Learning	Mar 2, 2025	Continual Learning	CodeCode Available	1	5
Adversarial Continual Learning	Mar 21, 2020	Continual Learningimage-classification	CodeCode Available	1	5
Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation	Jul 19, 2021	Continual LearningContinual Semantic Segmentation	CodeCode Available	1	5
Continual Domain Adaptation through Pruning-aided Domain-specific Weight Modulation	Apr 15, 2023	Continual LearningDomain Adaptation	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
ConPET: Continual Parameter-Efficient Tuning for Large Language Models	Sep 26, 2023	Continual Learning	CodeCode Available	1	5
Continual Learning of Diffusion Models with Generative Distillation	Nov 23, 2023	Continual LearningDenoising	CodeCode Available	1	5
Online Class-Incremental Continual Learning with Adversarial Shapley Value	Aug 31, 2020	Continual LearningOpen-Ended Question Answering	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
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
Consistent Prompting for Rehearsal-Free Continual Learning	Mar 13, 2024	Continual Learning	CodeCode Available	1	5
Computationally Budgeted Continual Learning: What Does Matter?	Mar 20, 2023	Continual LearningGPU	CodeCode Available	1	5
Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation	Oct 13, 2022	Class-Incremental Semantic SegmentationContinual Learning	CodeCode Available	1	5
Conditional Channel Gated Networks for Task-Aware Continual Learning	Mar 31, 2020	Continual Learning	CodeCode Available	1	5
ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis	Aug 25, 2023	Continual LearningPrognosis	CodeCode Available	1	5
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix	Oct 7, 2020	Continual Learning	CodeCode Available	1	5
CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning	Mar 15, 2024	class-incremental learningClass Incremental 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
A Theoretical Study on Solving Continual Learning	Nov 4, 2022	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
Asynchronous Federated Continual Learning	Apr 7, 2023	Continual LearningFederated Learning	CodeCode Available	1	5
Automatic Recall Machines: Internal Replay, Continual Learning and the Brain	Jun 22, 2020	Continual Learning	CodeCode Available	1	5
Compositional Language Continual Learning	May 1, 2020	Continual LearningMachine Translation	CodeCode Available	1	5
Continual Action Assessment via Task-Consistent Score-Discriminative Feature Distribution Modeling	Sep 29, 2023	Action AssessmentAction Quality Assessment	CodeCode Available	1	5
Continual evaluation for lifelong learning: Identifying the stability gap	May 26, 2022	Continual LearningIncremental Learning	CodeCode Available	1	5
Co2L: Contrastive Continual Learning	Jan 1, 2021	Continual LearningContrastive Learning	CodeCode Available	1	5
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning	Nov 23, 2022	Continual LearningNovel Concepts	CodeCode Available	1	5
CNLL: A Semi-supervised Approach For Continual Noisy Label Learning	Apr 21, 2022	Continual Learning	CodeCode Available	1	5
CLR: Channel-wise Lightweight Reprogramming for Continual Learning	Jul 21, 2023	Continual Learningimage-classification	CodeCode Available	1	5
Co^2L: Contrastive Continual Learning	Jun 28, 2021	Continual LearningContrastive Learning	CodeCode Available	1	5
CoDeC: Communication-Efficient Decentralized Continual Learning	Mar 27, 2023	Continual LearningFederated Learning	CodeCode Available	1	5
CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning	May 30, 2025	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
CL-MASR: A Continual Learning Benchmark for Multilingual ASR	Oct 25, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1	5
ARCADe: A Rapid Continual Anomaly Detector	Aug 10, 2020	Anomaly Detectioncontinual anomaly detection	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

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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