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 251–300 of 2644 papers

Title	Date	Tasks	Status	Hype
Latest Advancements Towards Catastrophic Forgetting under Data Scarcity: A Comprehensive Survey on Few-Shot Class Incremental Learning	Feb 12, 2025	class-incremental learningClass Incremental Learning	—Unverified	0
Analysis of Overparameterization in Continual Learning under a Linear Model	Feb 11, 2025	Continual Learningregression	—Unverified	0
Memory Is Not the Bottleneck: Cost-Efficient Continual Learning via Weight Space Consolidation	Feb 11, 2025	class-incremental learningClass Incremental Learning	—Unverified	0
Prompt-Driven Continual Graph Learning	Feb 10, 2025	Continual LearningGraph Learning	CodeCode Available	0
Federated Continual Learning: Concepts, Challenges, and Solutions	Feb 10, 2025	Continual LearningFederated Learning	—Unverified	0
MixLLM: Dynamic Routing in Mixed Large Language Models	Feb 9, 2025	Continual Learning	—Unverified	0
No Images, No Problem: Retaining Knowledge in Continual VQA with Questions-Only Memory	Feb 6, 2025	Continual LearningQuestion Answering	CodeCode Available	0
Efficient Few-Shot Continual Learning in Vision-Language Models	Feb 6, 2025	Continual LearningImage Captioning	—Unverified	0
SPARC: Subspace-Aware Prompt Adaptation for Robust Continual Learning in LLMs	Feb 5, 2025	Continual Learning	—Unverified	0
MaintaAvatar: A Maintainable Avatar Based on Neural Radiance Fields by Continual Learning	Feb 4, 2025	Continual LearningNeRF	—Unverified	0
Activation-Informed Merging of Large Language Models	Feb 4, 2025	Computational EfficiencyContinual Learning	CodeCode Available	1
Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss	Feb 3, 2025	Atari GamesContinual Learning	—Unverified	0
Structural features of the fly olfactory circuit mitigate the stability-plasticity dilemma in continual learning	Feb 3, 2025	Continual LearningLifelong learning	—Unverified	0
Online Curvature-Aware Replay: Leveraging 2^nd Order Information for Online Continual Learning	Feb 3, 2025	Continual Learning	—Unverified	0
VLM-Assisted Continual learning for Visual Question Answering in Self-Driving	Feb 2, 2025	Autonomous DrivingContinual Learning	—Unverified	0
Agential AI for Integrated Continual Learning, Deliberative Behavior, and Comprehensible Models	Jan 28, 2025	Continual Learning	—Unverified	0
Random Walk Guided Hyperbolic Graph Distillation	Jan 26, 2025	Continual LearningGraph Learning	CodeCode Available	0
Active Learning for Continual Learning: Keeping the Past Alive in the Present	Jan 24, 2025	Active LearningContinual Learning	—Unverified	0
Low-rank Prompt Interaction for Continual Vision-Language Retrieval	Jan 24, 2025	Continual LearningContrastive Learning	CodeCode Available	1
Spurious Forgetting in Continual Learning of Language Models	Jan 23, 2025	Continual Learning	CodeCode Available	2
S-LoRA: Scalable Low-Rank Adaptation for Class Incremental Learning	Jan 22, 2025	class-incremental learningClass Incremental Learning	—Unverified	0
Multiple Queries with Multiple Keys: A Precise Prompt Matching Paradigm for Prompt-based Continual Learning	Jan 22, 2025	Continual Learning	—Unverified	0
Memory Storyboard: Leveraging Temporal Segmentation for Streaming Self-Supervised Learning from Egocentric Videos	Jan 21, 2025	Continual LearningContrastive Learning	CodeCode Available	0
Optimally-Weighted Maximum Mean Discrepancy Framework for Continual Learning	Jan 21, 2025	BenchmarkingContinual Learning	—Unverified	0
A margin-based replacement for cross-entropy loss	Jan 21, 2025	Adversarial RobustnessContinual Learning	—Unverified	0
CLOFAI: A Dataset of Real And Fake Image Classification Tasks for Continual Learning	Jan 19, 2025	Continual Learningimage-classification	CodeCode Available	0
Dynamic Continual Learning: Harnessing Parameter Uncertainty for Improved Network Adaptation	Jan 18, 2025	Continual Learning	—Unverified	0
Resource-Constrained Federated Continual Learning: What Does Matter?	Jan 15, 2025	Continual LearningGPU	—Unverified	0
Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model	Jan 15, 2025	Continual LearningTransfer Learning	—Unverified	0
Continual Deep Active Learning for Medical Imaging: Replay-Base Architecture for Context Adaptation	Jan 14, 2025	Active Learningclass-incremental learning	CodeCode Available	0
Continual Learning with Embedding Layer Surgery and Task-wise Beam Search using Whisper	Jan 14, 2025	Continual LearningDecoder	—Unverified	0
Dynamic Prototype Rehearsal for Continual Learning in ECG Arrhythmia Detection	Jan 13, 2025	Arrhythmia DetectionContinual Learning	—Unverified	0
Information-Theoretic Dual Memory System for Continual Learning	Jan 13, 2025	Continual Learning	—Unverified	0
TiEBe: Tracking Language Model Recall of Notable Worldwide Events Through Time	Jan 13, 2025	Continual LearningLanguage Modeling	CodeCode Available	0
CSTA: Spatial-Temporal Causal Adaptive Learning for Exemplar-Free Video Class-Incremental Learning	Jan 13, 2025	class-incremental learningClass Incremental Learning	CodeCode Available	0
Soup to go: mitigating forgetting during continual learning with model averaging	Jan 9, 2025	Continual LearningTask Arithmetic	—Unverified	0
LSEBMCL: A Latent Space Energy-Based Model for Continual Learning	Jan 9, 2025	Continual Learning	—Unverified	0
Online Continual Learning: A Systematic Literature Review of Approaches, Challenges, and Benchmarks	Jan 9, 2025	Continual Learningimage-classification	CodeCode Available	1
Towards Balanced Continual Multi-Modal Learning in Human Pose Estimation	Jan 9, 2025	3D Human Pose Estimation3D Pose Estimation	—Unverified	0
Continuous Knowledge-Preserving Decomposition for Few-Shot Continual Learning	Jan 9, 2025	class-incremental learningClass Incremental Learning	CodeCode Available	1
Supervised Learning with Evolving Tasks and Performance Guarantees	Jan 9, 2025	Continual LearningMulti-Task Learning	CodeCode Available	0
Federated-Continual Dynamic Segmentation of Histopathology guided by Barlow Continuity	Jan 8, 2025	Continual Learning	—Unverified	0
Improving GenIR Systems Based on User Feedback	Jan 6, 2025	Continual LearningPrompt Learning	—Unverified	0
Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual Learning	Jan 4, 2025	Continual LearningMixture-of-Experts	—Unverified	0
ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think	Jan 2, 2025	Continual Learning	—Unverified	0
MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware Classification	Jan 2, 2025	class-incremental learningClass Incremental Learning	CodeCode Available	1
H2ST: Hierarchical Two-Sample Tests for Continual Out-of-Distribution Detection	Jan 1, 2025	Continual LearningIncremental Learning	CodeCode Available	0
Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning	Jan 1, 2025	class-incremental learningClass Incremental Learning	—Unverified	0
Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor	Jan 1, 2025	Continual LearningFederated Learning	—Unverified	0
BiLoRA: Almost-Orthogonal Parameter Spaces for Continual Learning	Jan 1, 2025	Continual Learningparameter-efficient fine-tuning	—Unverified	0

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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