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 1001–1050 of 2644 papers

Title	Date	Tasks	Status
Continual learning with the neural tangent ensemble	Aug 30, 2024	Continual Learningvalid	—Unverified
Novel-WD: Exploring acquisition of Novel World Knowledge in LLMs Using Prefix-Tuning	Aug 30, 2024	Causal Language ModelingContinual Learning	—Unverified
Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual Learning	Aug 29, 2024	Continual LearningMulti-Task Learning	CodeCode Available
Adaptive Variational Continual Learning via Task-Heuristic Modelling	Aug 29, 2024	Continual LearningModel Optimization	—Unverified
Maelstrom Networks	Aug 29, 2024	Continual LearningInductive Bias	—Unverified
LM-PUB-QUIZ: A Comprehensive Framework for Zero-Shot Evaluation of Relational Knowledge in Language Models	Aug 28, 2024	Continual LearningKnowledge Probing	—Unverified
Continual-learning-based framework for structural damage recognition	Aug 28, 2024	Continual Learning	—Unverified
Prior-free Balanced Replay: Uncertainty-guided Reservoir Sampling for Long-Tailed Continual Learning	Aug 27, 2024	class-incremental learningClass Incremental Learning	—Unverified
Dual-CBA: Improving Online Continual Learning via Dual Continual Bias Adaptors from a Bi-level Optimization Perspective	Aug 26, 2024	Continual Learning	—Unverified
May the Forgetting Be with You: Alternate Replay for Learning with Noisy Labels	Aug 26, 2024	Continual LearningLearning with noisy labels	—Unverified
A Unified Framework for Continual Learning and Unlearning	Aug 21, 2024	Continual LearningKnowledge Distillation	—Unverified
CluMo: Cluster-based Modality Fusion Prompt for Continual Learning in Visual Question Answering	Aug 21, 2024	Continual LearningQuestion Answering	CodeCode Available
Overcoming Growth-Induced Forgetting in Task-Agnostic Continual Learning	Aug 20, 2024	Continual Learning	—Unverified
Mitigating the Stability-Plasticity Dilemma in Adaptive Train Scheduling with Curriculum-Driven Continual DQN Expansion	Aug 19, 2024	Continual LearningScheduling	—Unverified
Boosting Open-Domain Continual Learning via Leveraging Intra-domain Category-aware Prototype	Aug 19, 2024	Continual Learning	—Unverified
Continual Dialogue State Tracking via Reason-of-Select Distillation	Aug 19, 2024	Continual LearningDialogue State Tracking	CodeCode Available
E-CGL: An Efficient Continual Graph Learner	Aug 18, 2024	Continual LearningGraph Learning	CodeCode Available
TACOS: Task Agnostic Continual Learning in Spiking Neural Networks	Aug 16, 2024	Continual LearningIncremental Learning	—Unverified
Learning to Route for Dynamic Adapter Composition in Continual Learning with Language Models	Aug 16, 2024	Continual Learningparameter-efficient fine-tuning	—Unverified
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?	Aug 14, 2024	Continual LearningGaussian Processes	CodeCode Available
Towards Effective Authorship Attribution: Integrating Class-Incremental Learning	Aug 12, 2024	Authorship Attributionclass-incremental learning	CodeCode Available
SRTFD: Scalable Real-Time Fault Diagnosis through Online Continual Learning	Aug 11, 2024	Continual LearningFault Diagnosis	—Unverified
Continual Learning of Nonlinear Independent Representations	Aug 11, 2024	Continual LearningLifelong learning	—Unverified
The Need for a Big World Simulator: A Scientific Challenge for Continual Learning	Aug 6, 2024	Continual Learning	—Unverified
Learning to Learn without Forgetting using Attention	Aug 6, 2024	Continual LearningMeta-Learning	CodeCode Available
Distribution-Level Memory Recall for Continual Learning: Preserving Knowledge and Avoiding Confusion	Aug 4, 2024	Continual Learning	—Unverified
Exploiting the Semantic Knowledge of Pre-trained Text-Encoders for Continual Learning	Aug 2, 2024	Continual LearningKnowledge Distillation	CodeCode Available
PMoE: Progressive Mixture of Experts with Asymmetric Transformer for Continual Learning	Jul 31, 2024	Continual LearningGeneral Knowledge	—Unverified
VIPeR: Visual Incremental Place Recognition with Adaptive Mining and Continual Learning	Jul 31, 2024	Continual LearningKnowledge Distillation	—Unverified
PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning	Jul 30, 2024	class-incremental learningClass Incremental Learning	CodeCode Available
An Effective Dynamic Gradient Calibration Method for Continual Learning	Jul 30, 2024	Continual Learning	—Unverified
Distribution-Aware Replay for Continual MRI Segmentation	Jul 30, 2024	Continual LearningHippocampus	—Unverified
Constructing Enhanced Mutual Information for Online Class-Incremental Learning	Jul 26, 2024	class-incremental learningClass Incremental Learning	—Unverified
PromptCCD: Learning Gaussian Mixture Prompt Pool for Continual Category Discovery	Jul 26, 2024	Continual LearningRepresentation Learning	CodeCode Available
Continual Learning with Hebbian Plasticity in Sparse and Predictive Coding Networks: A Survey and Perspective	Jul 24, 2024	Continual LearningSurvey	—Unverified
Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel Perspective	Jul 24, 2024	Continual Learningparameter-efficient fine-tuning	—Unverified
Local vs Global continual learning	Jul 23, 2024	Continual Learning	—Unverified
CLIP with Generative Latent Replay: a Strong Baseline for Incremental Learning	Jul 22, 2024	Class Incremental LearningContinual Learning	—Unverified
A Life-long Learning Intrusion Detection System for 6G-Enabled IoV	Jul 22, 2024	class-incremental learningClass Incremental Learning	—Unverified
Enhancing Hardware Fault Tolerance in Machines with Reinforcement Learning Policy Gradient Algorithms	Jul 21, 2024	Continual LearningOpenAI Gym	—Unverified
Flatness-aware Sequential Learning Generates Resilient Backdoors	Jul 20, 2024	Continual Learning	CodeCode Available
Continual Panoptic Perception: Towards Multi-modal Incremental Interpretation of Remote Sensing Images	Jul 19, 2024	Caption GenerationContinual Learning	CodeCode Available
An Attention-based Representation Distillation Baseline for Multi-Label Continual Learning	Jul 19, 2024	Continual LearningTransfer Learning	CodeCode Available
Continual Learning for Remote Physiological Measurement: Minimize Forgetting and Simplify Inference	Jul 19, 2024	class-incremental learningClass Incremental Learning	CodeCode Available
Learn to Memorize and to Forget: A Continual Learning Perspective of Dynamic SLAM	Jul 18, 2024	Continual LearningSimultaneous Localization and Mapping	—Unverified
Continual Distillation Learning: Knowledge Distillation in Prompt-based Continual Learning	Jul 18, 2024	Continual LearningKnowledge Distillation	—Unverified
FETCH: A Memory-Efficient Replay Approach for Continual Learning in Image Classification	Jul 17, 2024	BenchmarkingContinual Learning	—Unverified
An Evaluation of Continual Learning for Advanced Node Semiconductor Defect Inspection	Jul 17, 2024	Continual LearningMeta-Learning	—Unverified
Continual Learning for Temporal-Sensitive Question Answering	Jul 17, 2024	Continual LearningContrastive Learning	—Unverified
Continual Learning for Adaptable Car-Following in Dynamic Traffic Environments	Jul 17, 2024	Autonomous DrivingContinual Learning	—Unverified

Show:10 25 50

← PrevPage 21 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