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 151–200 of 2644 papers

Title	Date	Tasks	Status	Hype
Continual Learning via Sequential Function-Space Variational Inference	Dec 28, 2023	Bayesian InferenceContinual Learning	CodeCode Available	1
Continual Learning: Forget-free Winning Subnetworks for Video Representations	Dec 19, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1
Prediction and Control in Continual Reinforcement Learning	Dec 18, 2023	Continual LearningGeneral Knowledge	CodeCode Available	1
What to Remember: Self-Adaptive Continual Learning for Audio Deepfake Detection	Dec 15, 2023	Audio Deepfake DetectionContinual Learning	CodeCode Available	1
Weighted Ensemble Models Are Strong Continual Learners	Dec 14, 2023	Continual Learning	CodeCode Available	1
LAMM: Label Alignment for Multi-Modal Prompt Learning	Dec 13, 2023	Continual LearningPrompt Learning	CodeCode Available	1
Improving Plasticity in Online Continual Learning via Collaborative Learning	Dec 1, 2023	Continual Learning	CodeCode Available	1
Automating Continual Learning	Dec 1, 2023	Continual Learningimage-classification	CodeCode Available	1
Continual Self-supervised Learning: Towards Universal Multi-modal Medical Data Representation Learning	Nov 29, 2023	Continual LearningContinual Self-Supervised Learning	CodeCode Available	1
Continual Learning for Image Segmentation with Dynamic Query	Nov 29, 2023	Continual LearningDiversity	CodeCode Available	1
Continual Learning of Diffusion Models with Generative Distillation	Nov 23, 2023	Continual LearningDenoising	CodeCode Available	1
Prompt Pool based Class-Incremental Continual Learning for Dialog State Tracking	Nov 17, 2023	Continual Learningdialog state tracking	CodeCode Available	1
Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models	Nov 14, 2023	Continual LearningQuestion Answering	CodeCode Available	1
Continual atlas-based segmentation of prostate MRI	Nov 1, 2023	Continual Learningimage-classification	CodeCode Available	1
Fast Trainable Projection for Robust Fine-Tuning	Oct 29, 2023	Continual Learning	CodeCode Available	1
CL-MASR: A Continual Learning Benchmark for Multilingual ASR	Oct 25, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1
Continual Named Entity Recognition without Catastrophic Forgetting	Oct 23, 2023	Continual LearningContinual Named Entity Recognition	CodeCode Available	1
A Survey on Continual Semantic Segmentation: Theory, Challenge, Method and Application	Oct 22, 2023	Continual LearningContinual Semantic Segmentation	CodeCode Available	1
Orthogonal Subspace Learning for Language Model Continual Learning	Oct 22, 2023	Continual LearningLanguage Modeling	CodeCode Available	1
Towards a General Framework for Continual Learning with Pre-training	Oct 21, 2023	Continual Learningparameter-efficient fine-tuning	CodeCode Available	1
A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm	Oct 18, 2023	Continual LearningIncremental Learning	CodeCode Available	1
Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality	Oct 11, 2023	Continual Learning	CodeCode Available	1
TRACE: A Comprehensive Benchmark for Continual Learning in Large Language Models	Oct 10, 2023	Code GenerationContinual Learning	CodeCode Available	1
InfoCL: Alleviating Catastrophic Forgetting in Continual Text Classification from An Information Theoretic Perspective	Oct 10, 2023	ClassificationContinual Learning	CodeCode Available	1
Prompt-augmented Temporal Point Process for Streaming Event Sequence	Oct 8, 2023	Continual LearningPoint Processes	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
SCALE: Synergized Collaboration of Asymmetric Language Translation Engines	Sep 29, 2023	Continual LearningTranslation	CodeCode Available	1
DataDAM: Efficient Dataset Distillation with Attention Matching	Sep 29, 2023	Continual LearningDataset Distillation	CodeCode Available	1
Continual Action Assessment via Task-Consistent Score-Discriminative Feature Distribution Modeling	Sep 29, 2023	Action AssessmentAction Quality Assessment	CodeCode Available	1
ConPET: Continual Parameter-Efficient Tuning for Large Language Models	Sep 26, 2023	Continual Learning	CodeCode Available	1
Class Incremental Learning via Likelihood Ratio Based Task Prediction	Sep 26, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1
HPCR: Holistic Proxy-based Contrastive Replay for Online Continual Learning	Sep 26, 2023	Continual Learning	CodeCode Available	1
FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning	Sep 25, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1
DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues	Sep 18, 2023	Continual LearningContrastive Learning	CodeCode Available	1
CaT: Balanced Continual Graph Learning with Graph Condensation	Sep 18, 2023	Continual LearningGraph Learning	CodeCode Available	1
FedJudge: Federated Legal Large Language Model	Sep 15, 2023	Continual LearningFederated Learning	CodeCode Available	1
EgoObjects: A Large-Scale Egocentric Dataset for Fine-Grained Object Understanding	Sep 15, 2023	Continual LearningObject	CodeCode Available	1
Mitigating the Alignment Tax of RLHF	Sep 12, 2023	Common Sense ReasoningContinual Learning	CodeCode Available	1
Class-Incremental Grouping Network for Continual Audio-Visual Learning	Sep 11, 2023	audio-visual learningclass-incremental learning	CodeCode Available	1
Rethinking Momentum Knowledge Distillation in Online Continual Learning	Sep 6, 2023	Continual LearningKnowledge Distillation	CodeCode Available	1
Continual Evidential Deep Learning for Out-of-Distribution Detection	Sep 6, 2023	Continual LearningDeep Learning	CodeCode Available	1
ScrollNet: Dynamic Weight Importance for Continual Learning	Aug 31, 2023	Continual Learning	CodeCode Available	1
Incorporating Neuro-Inspired Adaptability for Continual Learning in Artificial Intelligence	Aug 29, 2023	Continual Learning	CodeCode Available	1
ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis	Aug 25, 2023	Continual LearningPrognosis	CodeCode Available	1
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning	Aug 24, 2023	Continual LearningFederated Learning	CodeCode Available	1
Overcoming Generic Knowledge Loss with Selective Parameter Update	Aug 23, 2023	Continual LearningGeneral Knowledge	CodeCode Available	1
A Comprehensive Empirical Evaluation on Online Continual Learning	Aug 20, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1
NAPA-VQ: Neighborhood Aware Prototype Augmentation with Vector Quantization for Continual Learning	Aug 18, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning	Aug 18, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1
Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning	Aug 18, 2023	class-incremental learningClass Incremental 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