xialeiliu/Awesome-Incremental-Learning
TopGit tracks xialeiliu/Awesome-Incremental-Learning on GitHub. The project has 4.5k stars. Awesome Incremental Learning
Snapshot summary built from the project's own GitHub metadata — there's no written TopGit review yet. The page will update automatically when a full review is published.
TopGit writes full reviews for the most-starred, most-requested repositories. This page is a snapshot until then — see the READ ME tab for the original README in full.
Snapshot
Top contributors
Show top contributors
Awesome Incremental Learning / Lifelong learning
Survey
- Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting (arXiv 2025) [paper][code]
- Continual Learning With Knowledge Distillation: A Survey (TNNLS 2024) [paper]
- Recent Advances of Multimodal Continual Learning: A Comprehensive Survey (arXiv 2024) [paper]
- Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy (JBCS 2024) [paper]
- Class-Incremental Learning: A Survey (TPAMI 2024) [paper][code]
- Continual Learning with Pre-Trained Models: A Survey (IJCAI 2024) [paper][code]
- Continual Learning of Large Language Models: A Comprehensive Survey (arXiv 2024) [paper][code]
- A Comprehensive Survey of Continual Learning: Theory, Method and Application (TPAMI 2024) [paper]
- A Comprehensive Empirical Evaluation on Online Continual Learning (ICCV Workshop 2023) [paper][code]
- A Survey on Few-Shot Class-Incremental Learning (Neural Networks 2024) [paper]
- A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning (Neural Networks 2023) [paper]
- An Introduction to Lifelong Supervised Learning (arXiv 2022) [paper]
- A Survey on Incremental Update for Neural Recommender Systems (arXiv 2023) [paper]
- Continual Learning of Natural Language Processing Tasks: A Survey (arXiv 2022) [paper]
- Continual Learning for Real-World Autonomous Systems: Algorithms, Challenges and Frameworks (arXiv 2022) [paper]
- Recent Advances of Continual Learning in Computer Vision: An Overview (arXiv 2021) [paper]
- Replay in Deep Learning: Current Approaches and Missing Biological Elements (Neural Computation 2021) [paper]
- Online Continual Learning in Image Classification: An Empirical Survey (Neurocomputing 2021) [paper] [code]
- Continual Lifelong Learning in Natural Language Processing: A Survey (COLING 2020) [paper]
- Class-incremental learning: survey and performance evaluation (TPAMI 2022) [paper] [code]
- A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks (Neural Networks) [paper] [code]
- A continual learning survey: Defying forgetting in classification tasks (TPAMI 2021) [paper] [arxiv]
- Continual Lifelong Learning with Neural Networks: A Review (Neural Networks) [paper]
- Three scenarios for continual learning (Nature Machine Intelligence 2022) [paper][code]
Papers
2026
-
PrePrompt: Predictive Prompting for Class Incremental Learning. (KDD 2026) [paper] [code]
-
Parameterized Prompt for Incremental Object Detection (CVPR 2026) [paper] [code]
-
Is Parameter Isolation Better for Prompt-Based Continual Learning? (CVPR 2026) [paper]
-
Quantum-Gated Task-interaction Knowledge Distillation for Pre-trained Model-based Class-Incremental Learning (CVPR 2026) [paper][code]
-
Semantic-Guided Global-Local Collaborative Prompt Learning for Few-Shot Class Incremental Learning (CVPR 2026) [paper]
-
Octopus: History-Free Gradient Orthogonalization for Continual Learning in Multimodal Large Language Models (CVPR 2026) [paper]
-
Elastic Weight Consolidation Done Right for Continual Learning (CVPR 2026) [paper][code]
-
Quantized Residuals to Continuous Prompts for Few-Shot Class Incremental Learning in Vision-Language Models (CVPR 2026) [paper]
-
On Token’s Dilemma: Dynamic MoE with Drift-Aware Token Assignment for Continual Learning of Large Vision Language Models (CVPR 2026) [paper][code]
-
Affordance-First Decomposition for Continual Learning in Video–Language Understanding (CVPR 2026) [paper]
-
Lifelong Imitation Learning with Multimodal Latent Replay and Incremental Adjustment (CVPR 2026) [paper][code]
-
Seeing the Scene Matters: Revealing Forgetting in Video Understanding Models with a Scene-Aware Long-Video Benchmark (CVPR 2026) [paper]
-
Dual-Estimator: Decoupling Global and Local Semantic Shift for Drift Compensation in Class-Incremental Learning (CVPR 2026) [paper][code]
-
Multimodal Continual Instruction Tuning with Dynamic Gradient Guidance (CVPR 2026) [paper][[code](https: //github.com/lisongze/DGG)]
-
Continual Distillation of Teachers from Different Domains (CVPR 2026) [paper][code]
-
AdaPrior:Bayesian-InspiredAdaptivePriorCorrectionforLong-Tailed ContinualLearning (CVPR 2026) [paper]
-
Learning from Itself: Mining Internal Knowledge from Vision Language Models for Continual Learning (CVPR 2026) [paper][[code](https://github.com/ jordangong/continual-learning)]
-
An Optimal Transport-driven Approach for Cultivating Latent Space in Online Incremental Learning (CVPR 2026) [paper]
-
The Blind Spot of Adaptation: Quantifying and Mitigating Forgetting in Fine-tuned Driving Models (CVPR 2026) [paper]
-
Parameter-efficient Continual Learning for Enhancing Plasticity without Forgetting under Limited Model Capacity (CVPR 2026) [paper]
-
HAD:Heterogeneity-Aware Distillation for Lifelong Heterogeneous Learning (CVPR 2026) [paper]
-
Beyond the Static-World: Lifelong Learning for All-in-One Medical Image Restoration (CVPR 2026) [paper]
-
Towards an Incremental Unified Multimodal Anomaly Detection: Augmenting Multimodal Denoising From an Information Bottleneck Perspective (CVPR 2026) [paper]
-
EW-DETR:Evolving World Object Detection via Incremental Low-Rank DEtection TRansformer (CVPR 2026) [paper]
-
Representation-Steered Incremental Adapter-Tuning for Class-Incremental Learning with Pre-Trained Models (CVPR 2026) [paper][code]
-
Re-evaluating Continual VQA: Toward Fair and Robust Evaluation for Multimodal Continual Learning (CVPR 2026) [paper][code]
-
Enhancing Continual Learning of Vision-Language Models via Dynamic Prefix Weighting (CVPR 2026) [paper][code]
-
CGL: Advancing Continual GUI Learning via Reinforcement Fine-Tuning (CVPR 2026) [paper]
-
PACT: Phase-Like Transition Constraints in Adapter-Based Continual Learning of Vision-Language Models (CVPR 2026) [paper][code]
-
Critical Patch-Aware Sparse Prompting with Decoupled Training for Continual Learning on the Edge (CVPR 2026) [paper][code]
-
TAPE: Task-Adaptive Prototype Evolution in Audio-Language Models for Fully Few-shot Class-incremental Audio Classification (CVPR 2026) [paper][code]
-
Beyond Myopic Alignment: Lookahead Optimization for Online Class-Incremental Learning (CVPR 2026) [paper]
-
SAME:Sparse and Anchored Model Editing for Heterogeneous Incremental Learning under Limited Data (CVPR 2026) [paper]
-
Beyond Prompt Degradation: Prototype-guided Dual-pool Prompting for Incremental Object Detection (CVPR 2026) [paper][code]
-
Decouple Your Discovery and Memory in Continual Generalized Category Discovery (CVPR 2026) [paper]
-
TAPE: Task-Adaptive Prototype Evolution in Audio-Language Models for Fully Few-shot Class-incremental Audio Classification (CVPR 2026) [paper][code]
-
Resolving the Stability-Plasticity Dilemma in Reinforcement Learning via Complementary Continual Critics (CVPR 2026) [paper]
-
Resolving the Stability-Plasticity Dilemma in Reinforcement Learning via Complementary Continual Critics (CVPR 2026) [paper]
-
CHEEM:Continual Learning by Reuse, New, Adapt and Skip A Hierarchical Exploration-Exploitation Approach (CVPR 2026) [paper][code]
-
A Faster Path to Continual Learning (CVPR 2026) [paper]
-
Beyond the Static World: Continual Category Discovery under Visual Drift (CVPR 2026) [paper]
-
DGS: Dual Gradient and Semantic-Shift Guided Low-Rank Adaptation for Class Incremental Learning (CVPR 2026) [paper]
-
Robustness Under Data Scarcity: Few-Shot Continual Adversarial Training for Evolving Threats (CVPR 2026) [paper][code]
-
Subspace Alignment for CLIP-based Continual Learning via Canonical Correlation Analysis (CVPR 2026) [paper] [code]
-
Which Concepts to Forget and How to Refuse? Decomposing Concepts for Continual Unlearning in Large Vision-Language Models (CVPR 2026) [paper]
-
Temporal Imbalance of Positive and Negative Supervision in Class-Incremental Learning (CVPR 2026) [paper] [code]
-
Few-Shot Hybrid Incremental Learning: Continually Learning under Data Scarcity and Task Uncertainty (CVPR 2026) [paper]
-
HYCAL: ATraining-Free Prototype Calibration Method for Cross-Discipline Few-Shot Class-Incremental Learning (CVPR 2026) [paper]
-
Geometry-driven OOD Detectors Are Class-Incremental Learners (CVPR 2026) [paper][code]
-
Dynamic Magic: Unleashing Restricted Knowledge for Lifelong Person Re-Identification (CVPR 2026) [paper]
-
Forging a Dynamic Memory: Retrieval-Guided Continual Learning for Generalist Medical Foundation Models (CVPR 2026) [paper]
-
Incremental Object Detection via Future-Aware Decoupled Cross-Head Distillation (CVPR 2026) [paper]
-
Towards Dynamic Modality Alignment in Multimodal Continual Learning (CVPR 2026) [paper]
-
DK-DDIL: Adaptive Knowledge Retention for Dynamic Domain-Incremental Learning in Medical Imaging (CVPR 2026) [paper]
-
DSCA: Dynamic Subspace Concept Alignment for Lifelong VLM Editing (CVPR 2026) [paper]
-
BriMA: Bridged Modality Adaptation for Multi-Modal Continual Action Quality Assessment (CVPR 2026) [paper][code]
-
ϕ-DPO: Fairness Direct Preference Optimization Approach to Continual Learning in Large Multimodal Models (CVPR 2026) [paper]
-
InvCoSS: Inversion-driven Continual Self-supervised Learning in Medical Multi-modal Image Pre-training (CVPR 2026) [paper]
-
Spectral Mixture-of-Experts for Continual Learning (CVPR 2026) [paper][code]
-
One-Prompt Strikes Back: Sparse Mixture of Experts for Prompt-based Continual Learning (ICLR 2026) [paper][code]
-
Detect, Decide, Unlearn: A Transfer-Aware Framework for Continual Learning (ICLR 2026) [paper]
-
Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning (ICLR 2026) [paper][code]
-
Continual Unlearning for Text-to-Image Diffusion Models: A Regularization Perspective (ICLR 2026) [paper][code]
-
Rethinking Continual Learning with Progressive Neural Collapse (ICLR 2026) [paper][code]
-
Null-Space Filtering for Data-Free Continual Model Merging: Preserving Stability, Promoting Plasticity (ICLR 2026) [paper][code]
-
MergeTune: Continued Fine-Tuning of Vision-Language Models (ICLR 2026) [paper][code]
-
IDER: IDempotent Experience Replay for Reliable Continual Learning (ICLR 2026) [paper][code]
-
Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models (ICLR 2026) [paper]
-
XIL: Cross-Expanding Incremental Learning (ICLR 2026) [paper]
-
Interference-Isolated Elastic Weight Consolidation and Knowledge Calibration for Incremental Object Detection (ICLR 2026) [paper]
-
Mapping Post-Training Forgetting in Language Models at Scale (ICLR 2026) [paper][code]
-
PRISM: Progressive Robust Learning for Open-World Continual Category Discovery (ICLR 2026) [paper]
-
Consistency-Driven Calibration and Matching for Few-Shot Class Incremental Learning (ICLR 2026) [paper][code]
-
Heads collapse, features stay: Why Replay needs big buffers (ICLR 2026) [paper]
-
PAC-Bayes bounds for cumulative loss in Continual Learning (ICLR 2026) [paper]
-
HippoTune: A Hippocampal Associative Loop–Inspired Fine-Tuning Method for Continual Learning (ICLR 2026) [paper][code]
-
Fly-CL: A Fly-Inspired Framework for Enhancing Efficient Decorrelation and Reduced Training Time in Pre-trained Model-based Continual Representation Learning (ICLR 2026) [paper][code]
-
Two-Way Is Better Than One: Bidirectional Alignment with Cycle Consistency for Exemplar-Free Class-Incremental Learning (ICLR 2026) [paper][code]
-
Pi-CCA: Prompt-Invariant CCA Certificates for Replay-Free Continual Multimodal Learning (ICLR 2026) [paper]
-
The Lie of the Average: How Class Incremental Learning Evaluation Deceives You? (ICLR 2026) [paper][code]
-
CoMem: Compositional Concept-Graph Memory for Vision–Language Adaptation (ICLR 2026) [paper][code]
-
Quantized Gradient Projection for Memory-Efficient Continual Learning (ICLR 2026) [paper][code]
-
Reversible Primitive–Composition Alignment for Continual Vision–Language Learning (ICLR 2026) [paper]
-
RLAP-CLIP: Continual Multimodal Learning with Prototype Adaptation and Difficulty-Aware Routing (ICLR 2026) [paper]
-
KeepLoRA: Continual Learning with Residual Gradient Adaptation (ICLR 2026) [paper][code]
-
Asymmetric Synthetic Data Update for Domain Incremental Dataset Distillation (ICLR 2026) [paper]
-
LCA: Local Classifier Alignment for Continual Learning (ICLR 2026) [paper]
-
Revisiting Weight Regularization for Low-Rank Continual Learning (ICLR 2026) [paper][code]
-
Point-UQ: An Uncertainty-Quantification Paradigm for Point Cloud Few-Shot Class Incremental Learning (ICLR 2026) [paper]
-
Principled Fast and Meta Knowledge Learners for Continual Reinforcement Learning (ICLR 2026) [paper][code]
-
Plug-and-Play Compositionality for Boosting Continual Learning with Foundation Models (ICLR 2026) [paper][code]
-
Enhanced Continual Learning of Vision-Language Models with Model Fusion (ICLR 2026) [paper][code]
-
Naming to Learn: Class Incremental Learning for Vision-Language Model with Unlabeled Data (ICLR 2026) [paper][code]
-
StPR: Spatiotemporal Preservation and Routing for Exemplar-Free Video Class-Incremental Learning (ICLR 2026) [paper]
-
SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting (ICLR 2026) [paper][code]
-
Merge before Forget: A Single LoRA Continual Learning via Continual Merging (ICLR 2026) [paper]
-
Fed-Duet: Dual Expert-Orchestrated Framework for Continual Federated Vision-Language Learning (ICLR 2026) [paper][code]
-
Understanding the Dynamics of Forgetting and Generalization in Continual Learning via the Neural Tangent Kernel (ICLR 2026) [paper]
-
Activation Function Design Sustains Plasticity in Continual Learning (ICLR 2026) [paper]
-
FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning (ICLR 2026) [paper][code]
-
Active Continual Learning with Metaplastic Binary Bayesian Neural Networks (ICML 2026) [paper][code]
-
Advancing Analytic Class-Incremental Learning through Vision-Language Calibration (ICML 2026) [paper][code]
-
Adversarial Latent Embedding Repair for LLM Continual Learning (ICML 2026) [paper]
-
AREA: Attribute Extraction and Aggregation for CLIP-Based Class-Incremental Learning (ICML 2026) [paper][code]
-
Balancing Plasticity and Stability with Fast and Slow Successor Features (ICML 2026) [paper]
-
Beyond Buffer Limits: Energy-Based Data Reassembly for Continual Learning (ICML 2026) [paper]
-
Beyond Point-wise Neural Collapse: A Topology-Aware Hierarchical Classifier for Class-Incremental Learning (ICML 2026) [paper][code]
-
Breaking the Synthetic-Real Domain Shortcut for Training-Free Generative Replay-based Class Incremental Learning (ICML 2026) [paper]
-
BTSP-CAM: A Brain-Inspired Geometric Memory for Class-Incremental Learning (ICML 2026) [paper]
-
Calibrated Knowledge Aggregation in Bayesian Mixture-of-Experts for Continual VQA (ICML 2026) [paper]
-
Capacity-Agnostic Parameter Isolation for Continual Graph Learning (ICML 2026) [paper]
-
CE$^4$L: Continual Ego, Exo, and Ego-Exo Learning (ICML 2026) [paper][code]
-
Context Distillation Retains Post-Training Capabilities in Continually Trained LMs (ICML 2026) [paper]
-
Continual Learning of Domain-Invariant Representations (ICML 2026) [paper]
-
Continual Segmentation under Joint Nonstationarity (ICML 2026) [paper][code]
-
CoPE: Continual Probe-guided Expansion for Large Vision-Language Models (ICML 2026) [paper]
-
DiL: Discrete-anchored Representation Alignment for Semi-Supervised Continual Learning (ICML 2026) [paper]
-
Don't Forget Why You Started: Tackling Dual Forgetting in Vision-Language Continual Learning (ICML 2026) [paper]
-
ECA: Efficient Continual Alignment for Open-Ended Image-to-Text Generation. (ICML 2026) [paper][code]
-
Energy-Structured Low-Rank Adaptation for Continual Learning (ICML 2026) [paper]
-
Expandable, Compressible, Mineable: Open-World Thermal Infrared Image Restoration (ICML 2026) [paper]
-
Expert Routing with Synthetic Data for Domain Incremental Learning (ICML 2026) [paper]
-
ExSkill: Continual Learning from Experience and Skills in Multimodal Agents (ICML 2026) [paper][code]
-
Factor-Wise Homogeneity of Slot-Attention for Continual Object-Centric Learning (ICML 2026) [paper][code]
-
Focus, Align, and Sustain: Counteracting Gradient Dilution in Incremental Object Detection (ICML 2026) [paper]
-
GR-LoRA: Gradient-Recycling Low-Rank Adaptation for Class-Incremental Learning (ICML 2026) [paper][code]
-
HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning (ICML 2026) [paper][code]
-
Hierarchical Filtering and Refinement Classification for Few-Shot Class-Incremental Learning (ICML 2026) [paper][code]
-
HTAC: Hierarchical Task-Aware Composition for Continual Offline Reinforcement Learning (ICML 2026) [paper]
-
HypCL: Adapting CLIP in Hyperbolic Space for Continual Learning (ICML 2026) [paper]
-
Hyper-LLaVA: Hyperbolic Uncertainty-aware Modality-Balanced Routing for Multimodal Continual Instruction Tuning (ICML 2026) [paper]
-
Hyperbolic Multimodal Continual Learning (ICML 2026) [paper]
-
JANUS-LORA: A Balanced Low-Rank Adaptation for Continual Learning (ICML 2026) [paper]
-
Learnability-Driven Knowledge Assimilation for Class-Incremental Semantic Segmentation (ICML 2026) [paper]
-
Learning to Remember, Learn, and Forget in Attention-Based Models (ICML 2026) [paper]
-
Little By Little: Continual Learning via Incremental Mixture of Rank-1 Associative Memory Experts (ICML 2026) [paper][code]
-
MedCRP-CL: Continual Medical Image Segmentation via Bayesian Nonparametric Semantic Modality Discovery (ICML 2026) [paper][code]
-
Memory as a Markov Matrix: Sample Efficient Knowledge Expansion via Token-to-Dictionary Mapping (ICML 2026) [paper]
-
MePo: Meta Post-Refinement for Rehearsal-Free General Continual Learning (ICML 2026) [paper][code]
-
Merge to Remember: Sharpness-Aware Isotropic Merging for Continual Learning (ICML 2026) [paper][code]
-
Mitigating Plasticity Loss through Architectural Design in Continual Learning (ICML 2026) [paper]
-
MLUBench: A Benchmark for Lifelong Unlearning Evaluation in MLLMs (ICML 2026) [paper][code]
-
Model-Dowser: Data-Free Importance Probing to Mitigate Catastrophic Forgetting in Multimodal Large Language Models (ICML 2026) [paper]
-
Mixing Expertise with Confidence: A Mixture of Experts Framework for Robust Multi-Modal Continual Learning (ICML 2026) [paper]
-
MoCL: Metabolic Optimization for Curvature-Aware Continual Learning (ICML 2026) [paper]
-
Multi-Head Attention as a Source of Catastrophic Forgetting in MoE Transformers (ICML 2026) [paper]
-
Neuro-evolutionary Continual Reinforcement Learning (ICML 2026) [paper]
-
On the Power of Statistics in Class-Incremental Learning with Pretrained Models (ICML 2026) [paper]
-
On the Theory of Continual Learning with Gradient Descent for Neural Networks (ICML 2026) [paper]
-
Online Continual Learning with Dynamic Label Hierarchies (ICML 2026) [paper][code]
-
Parameter-Masked Decoupled Optimization for Cross-Domain Class-Incremental Learning (ICML 2026) [paper]
-
PLATE: Plasticity-Tunable Efficient Adapters for Geometry-Aware Continual Learning (ICML 2026) [paper][code]
-
Plasticity Activation via Polar Operator: A Plug-in Method for Balancing Stability and Plasticity (ICML 2026) [paper]
-
Preserving Plasticity in Continual Learning via Dynamical Isometry (ICML 2026) [paper]
-
Pretrained Vision-Language-Action Models are Surprisingly Resistant to Forgetting in Continual Learning (ICML 2026) [paper][code]
-
RAG without Forgetting: Continual Query-Infused Key Memory (ICML 2026) [paper]
-
Rethinking Memory in Continual Learning: Beyond a Monolithic Store of the Past (ICML 2026) [paper][code]
-
Retaining by Doing: The Role of On-Policy Data in Mitigating Forgetting (ICML 2026) [paper]
-
Retrospective Feature Estimation for Continual Learning (ICML 2026) [paper][code]
-
SABER: Continual Learning with Representation Conflict Management (ICML 2026) [paper]
-
SAME: Stabilized Mixture-of-Experts for Multimodal Continual Instruction Tuning (ICML 2026) [paper][code]
-
SAOT: Self-Supervised Continual Graph Learning with Structure-Aware Optimal Transport (ICML 2026) [paper]
-
Scaling Continual Learning with Bi-Level Routing Mixture-of-Experts (ICML 2026) [paper][code]
-
Self-Distillation Enables Continual Learning (ICML 2026) [paper][code]
-
Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfer (ICML 2026) [paper]
-
Shapley Neuron Values for Continual Learning: Which Neurons Matter Most? (ICML 2026) [paper]
-
Skill Neologisms: Towards Skill-based Continual Learning (ICML 2026) [paper][code]
-
Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning (ICML 2026) [paper]
-
Spectral Imbalance Causes Forgetting in Low-Rank Continual Adaptation (ICML 2026) [paper][code]
-
Subspace-Aware Feature Reshaping for Open-Set Graph Class-Incremental Learning (ICML 2026) [paper]
-
Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection (ICML 2026) [paper]
-
Task-Driven Subspace Decomposition for Knowledge Sharing and Isolation in LoRA-based Continual Learning (ICML 2026) [paper][code]
-
The Forgetting-Retention Dilemma: Certified Unlearning Theory in Continual Learning (ICML 2026) [paper]
-
Towards Understanding Continual Factual Knowledge Acquisition of Language Models: From Theory to Algorithm (ICML 2026) [paper][code]
-
Turning Back Without Forgetting: Selective Backward Refinement for Parameter-Efficient Continual Learning (ICML 2026) [paper][code]
-
Unlocking the Potential of Continual Model Merging: An ODE Perspective (ICML 2026) [paper]
2025
-
DitHub: A Modular Framework for Incremental Open-Vocabulary Object Detection (NeurIPS 2025) [paper][code]
-
Policy Compatible Skill Incremental Learning via Lazy Learning Interface (NeurIPS 2025) [paper][code]
-
Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental Learning (NeurIPS 2025) [paper]
-
Gated Integration of Low-Rank Adaptation for Continual Learning of Large Language Models (NeurIPS 2025) [paper]
-
MINGLE: Mixture of Null-Space Gated Low-Rank Experts for Test-Time Continual Model Merging (NeurIPS 2025) [paper][code]
-
Decentralized Dynamic Cooperation of Personalized Models for Federated Continual Learning (NeurIPS 2025) [paper][code]
-
Train with Perturbation, Infer after Merging: A Two-Stage Framework for Continual Learning (NeurIPS 2025) [paper][code]
-
MemEIC: A Step Toward Continual and Compositional Knowledge Editing (NeurIPS 2025) [paper][code]
-
C-NAV: Towards Self-Evolving Continual Object Navigation in Open World (NeurIPS 2025) [paper][code]
-
Hybrid Re-matching for Continual Learning with Parameter-Efficient Tuning (NeurIPS 2025) [paper][code]
-
A Minimalistic Unified Framework for Incremental Learning across Image Restoration Tasks (NeurIPS 2025) [paper]
-
REP: Resource-Efficient Prompting for Rehearsal-Free Continual Learning (NeurIPS 2025) [paper]
-
Learning Multi-Source and Robust Representations for Continual Learning (NeurIPS 2025) [paper][code]
-
Learning Expandable and Adaptable Representations for Continual Learning (NeurIPS 2025) [paper][code]
-
Dynamic Siamese Expansion Framework for Improving Robustness in Online Continual Learning (NeurIPS 2025) [paper]
-
Investigating and Mitigating Catastrophic Forgetting in Medical Knowledge Injection through Internal Knowledge Augmentation Learning (NeurIPS 2025) [paper][code]
-
C2Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning (NeurIPS 2025) [paper]
-
Bisecle: Binding and Separation in Continual Learning for Video Language Understanding (NeurIPS 2025) [paper]
-
Mixture of Noise for Pre-Trained Model-Based Class-Incremental Learning (NeurIPS 2025) [paper][code]
-
Continual Multimodal Contrastive Learning (NeurIPS 2025) [paper][code]
-
Class-wise Balancing Data Replay for Federated Class-Incremental Learning (NeurIPS 2025) [paper]
-
Model Inversion with Layer-Specific Modeling and Alignment for Data-Free Continual Learning (NeurIPS 2025) [paper][code]
-
Separating the 'what' and 'how' of compositional computation to enable reuse and continual learning (NeurIPS 2025) [paper]
-
Demystifying Language Model Forgetting with Low-rank Example Associations (NeurIPS 2025) [paper]
-
Resource-Constrained Federated Continual Learning: What Does Matter? (NeurIPS 2025) [paper]
-
GraphKeeper: Graph Domain-Incremental Learning via Knowledge Disentanglement and Preservation (NeurIPS 2025) [paper]
-
Turning the Tables: Enabling Backward Transfer via Causal-Aware LoRA in Continual Learning (NeurIPS 2025) [paper]
-
Mitigating Intra- and Inter-modal Forgetting in Continual Learning of Unified Multimodal Models (NeurIPS 2025) [paper][code]
-
AnaCP: Toward Upper-Bound Continual Learning via Analytic Contrastive Projection (NeurIPS 2025) [paper]
-
Contrastive Consolidation of Top-Down Modulations Achieves Sparsely Supervised Continual Learning (NeurIPS 2025) [paper]
-
Gradient-Guided Epsilon Constraint Method for Online Continual Learning (NeurIPS 2025) [paper]
-
Temporal-Difference Variational Continual Learning (NeurIPS 2025) [paper]
-
Confusion-Driven Self-Supervised Progressively Weighted Ensemble Learning for Non-Exemplar Class Incremental Learning (NeurIPS 2025) [paper]
-
Exploiting Task Relationships in Continual Learning via Transferability-Aware Task Embeddings (NeurIPS 2025) [paper][code]
-
MEMOIR: Lifelong Model Editing with Minimal Overwrite and Informed Retention for LLMs (NeurIPS 2025) [paper]
-
Self-Evolving Pseudo-Rehearsal for Catastrophic Forgetting with Task Similarity in LLMs (NeurIPS 2025) [paper][code]
-
Continual Gaussian Mixture Distribution Modeling for Class Incremental Semantic Segmentation (NeurIPS 2025) [paper]
-
Continuous Subspace Optimization for Continual Learning (NeurIPS 2025) [paper]
-
Dual-Space Semantic Synergy Distillation for Continual Learning of Unlabeled Streams (NeurIPS 2025) [paper]
-
Class-wise Balancing Data Replay for Federated Class-Incremental Learning (NeurIPS 2025) [paper]
-
Continual Knowledge Adaptation for Reinforcement Learning (NeurIPS 2025) [paper][code]
-
Learn and Ensemble Bridge Adapters for Multi-domain Task Incremental Learning (NeurIPS 2025) [paper]
-
Merging on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging (NeurIPS 2025) [paper][code]
-
Federated Continual Learning via Orchestrating Multi-Scale Expertise (NeurIPS 2025) [paper]
-
Reliable Lifelong Multimodal Editing: Conflict-Aware Retrieval Meets Multi-Level Guidance (NeurIPS 2025) [paper]
-
Evolving and Regularizing Meta-Environment Learner for Fine-Grained Few-Shot Class-Incremental Learning (NeurIPS 2025) [paper]
-
Diffusion-Classifier Synergy: Reward-Aligned Learning via Mutual Boosting Loop for FSCIL (NeurIPS 2025) [paper]
-
Continual Model Merging without Data: Dual Projections for Balancing Stability and Plasticity (NeurIPS 2025) [paper]
-
Mind the Gap: Preserving and Compensating for the Modality Gap in CLIP-Based Continual Learning (ICCV 2025) [paper][code]
-
Progressive Homeostatic and Plastic Prompt Tuning for Audio-Visual Multi-Task Incremental Learning (ICCV 2025) [paper][code]
-
Achieving More with Less: Additive Prompt Tuning for Rehearsal-Free Class-Incremental Learning (ICCV 2025) [paper][code]
-
RainbowPrompt: Diversity-Enhanced Prompt-Evolving for Continual Learning (ICCV 2025) [paper]
-
NavMorph: A Self-Evolving World Model for Vision-and-Language Navigation in Continuous Environments (ICCV 2025) [paper][code]
-
VA-MoE: Variables-Adaptive Mixture of Experts for Incremental Weather Forecasting (ICCV 2025) [paper][code]
-
FG-OrIU: Towards Better Forgetting via Feature-Gradient Orthogonality for Incremental Unlearning (ICCV 2025) [paper][code]
-
SMoLoRA: Exploring and Defying Dual Catastrophic Forgetting in Continual Visual Instruction Tuning (ICCV 2025) [paper][code]
-
PROL : Rehearsal Free Continual Learning in Streaming Data via Prompt Online Learning (ICCV 2025) [paper][code]
-
CL-Splats: Continual Learning of Gaussian Splatting with Local Optimization (ICCV 2025) [paper][code]
-
DMNSP: Dynamic Multi-Layer Null Space Projection for Vision-Language Continual Learning (ICCV 2025) [paper][code]
-
Ask and Remember: A Questions-Only Replay Strategy for Continual Visual Question Answering (ICCV 2025) [paper][code]
-
Causal Disentanglement and Cross-Modal Alignment for Enhanced Few-Shot Learning (ICCV 2025) [paper][code]
-
TWIST&SCOUT:GroundingMultimodal LLM-Experts by Forget-Free Tuning (ICCV 2025) [paper]
-
Adversarial Robust Memory-Based Continual Learner (ICCV 2025) [paper]
-
CRAM:Large-scale Video Continual Learning with Bootstrapped Compression (ICCV 2025) [paper]
-
iManip: Skill-Incremental Learning for Robotic Manipulation (ICCV 2025) [paper]
-
Hierarchical Visual Prompt Learning for Continual Video Instance Segmentation (ICCV 2025) [paper][code]
-
DuET: Dual Incremental Object Detection via Exemplar-Free Task Arithmetic (ICCV 2025) [paper]
-
Self-Reinforcing Prototype Evolution with Dual-Knowledge Cooperation for Semi-Supervised Lifelong Person Re-Identification (ICCV 2025) [paper][code]
-
Revisiting Pool-based Prompt Learning for Few-shot Class-incremental Learning (ICCV 2025) [paper][code]
-
Integrating Task-Specific and Universal Adapters for Pre-Trained Model-based Class-Incremental Learning (ICCV 2025) [paper][code]
-
Joint Diffusion Models in Continual Learning (ICCV 2025) [paper]
-
External Knowledge Injection for CLIP-Based Class-Incremental Learning (ICCV 2025) [paper][code]
-
Divide-and-Conquer for Enhancing Unlabeled Learning, Stability, and Plasticity in Semi-supervised Continual Learning (ICCV 2025) [paper][code]
-
Instruction-Grounded Visual Projectors for Continual Learning of Generative Vision-Language Models (ICCV 2025) [paper]
-
CODE-CL: Conceptor-Based Gradient Projection for Deep Continual Learning (ICCV 2025) [paper][code]
-
Dual Domain Control via Active Learning for Remote Sensing Domain Incremental Object Detection (ICCV 2025) [paper]
-
Feature Decomposition-Recomposition in Large Vision-Language Model for Few-Shot Class-Incremental Learning (ICCV 2025) [paper]
-
Seeing 3D Through 2D Lenses: 3D Few-Shot Class-Incremental Learning via Cross-Modal Geometric Rectification (ICCV 2025) [paper]
-
PLAN: Proactive Low-Rank Allocation for Continual Learning (ICCV 2025) [paper]
-
Overcoming Dual Drift for Continual Long-Tailed Visual Question Answering (ICCV 2025) [paper]
-
Continual Personalization for Diffusion Models (ICCV 2025) [paper]
-
Task-Aware Prompt Gradient Projection for Parameter-Efficient Tuning Federated Class-Incremental Learning (ICCV 2025) [paper]
-
Lark: Low-Rank Updates After Knowledge Localization for Few-shot Class-Incremental Learning (ICCV 2025) [paper]
-
CoSMIC: Continual Self-supervised Learning for Multi-Domain Medical Imaging via Conditional Mutual Information Maximization (ICCV 2025) [paper]
-
Flexi-FSCIL: Adaptive Knowledge Retention for Breaking the Stability-Plasticity Dilemma in Few-Shot Class-Incremental Learning (ICCV 2025) [paper]
-
Generalization-Preserved Learning: Closing the Backdoor to Catastrophic Forgetting in Continual Deepfake Detection (ICCV 2025) [paper]
-
A Tiny Change, A Giant Leap: Long-Tailed Class-Incremental Learning via Geometric Prototype Alignment (ICCV 2025) [paper]
-
Knowledge Decoupling via Orthogonal Projection for Lifelong Editing of Large Language Models (ACL 2025) [paper]
-
Serial Lifelong Editing via Mixture of Knowledge Expert (ACL 2025) [paper]
-
Efficient Domain Continual pretraining by Mitigating the Stability Gap (ACL 2025) [paper]
-
Neuron-Level Sequential Editing for Large Language Models (ACL 2025) [paper][code]
-
Controlled Low-Rank Adaptation with Subspace Regularization for Continued Training on Large Language Models (ACL 2025) [paper][code]
-
HiDe-LLaVA: Hierarchical Decoupling for Continual Instruction Tuning of Multimodal Large Language Model (ACL 2025) [paper][code]
-
Multi-Modality Expansion and Retention for LLMs through Parameter Merging and Decoupling (ACL 2025) [paper]
-
Continual Gradient Low-Rank Projection Fine-Tuning for LLMs (ACL 2025) [paper][code]
-
A Generative Adaptive Replay Continual Learning Model for Temporal Knowledge Graph Reasoning (ACL 2025) [paper][code]
-
Learn to Memorize: Scalable Continual Learning in Semiparametric Models with Mixture-of-Neighbors Induction Memory (ACL 2025) [paper][code]
-
Don't Half-listen: Capturing Key-part Information in Continual Instruction Tuning (ACL 2025) [paper]
-
Recurrent Knowledge Identification and Fusion for Language Model Continual Learning (ACL 2025) [paper][code]
-
TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining (ACL 2025) [paper][code]
-
Exploiting Presentative Feature Distributions for Parameter-Efficient Continual Learning of Large Language Models (ICML 2025) [paper][code]
-
Towards Understanding Catastrophic Forgetting in Two-layer Convolutional Neural Networks (ICML 2025) [paper]
-
Predicting the Susceptibility of Examples to Catastrophic Forgetting (ICML 2025) [paper]
-
Tensor Decomposition Based Memory-Efficient Incremental Learning (ICML 2025) [paper]
-
Navigating Semantic Drift in Task-Agnostic Class-Incremental Learning (ICML 2025) [paper][code]
-
Componential Prompt-Knowledge Alignment for Domain Incremental Learning (ICML 2025) [paper][code]
-
LADA: Scalable Label-Specific CLIP Adapter for Continual Learning (ICML 2025) [paper][code]
-
Reinforced Lifelong Editing for Language Models (ICML 2025) [paper][code]
-
Geometric Feature Embedding for Effective 3D Few-Shot Class Incremental Learning (ICML 2025) [paper][code]
-
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts (ICML 2025) [paper]
-
Unlocking the Power of Rehearsal in Continual Learning: ATheoretical Perspective (ICML 2025) [paper]
-
Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting (ICML 2025) [paper]
-
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn (ICML 2025) [paper][code]
-
A Selective Learning Method for Temporal Graph Continual Learning (ICML 2025) [paper]
-
Continual Reinforcement Learning by Planning with Online World Models (ICML 2025) [paper]
-
Knowledge Retention in Continual Model-Based Reinforcement Learning (ICML 2025) [paper]
-
SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning (ICML 2025) [paper][code]
-
Demystifying Catastrophic Forgetting in Two-Stage Incremental Object Detector (ICML 2025) [paper][code]
-
Understanding the Limits of Lifelong Knowledge Editing in LLMs (ICML 2025) [paper][code]
-
Knowledge Swapping via Learning and Unlearning (ICML 2025) [paper][code]
-
BECAME: Bayesian Continual Learning with Adaptive Model Merging (ICML 2025) [paper][code]
-
L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning (ICML 2025) [paper][code]
-
Optimal Task Order for Continual Learning of Multiple Tasks (ICML 2025) [paper]
-
The Importance of Being Lazy: Scaling Limits of Continual Learning (ICML 2025) [paper]
-
Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers (ICML 2025) [paper]
-
Learning Dynamics in Continual Pre-Training for Large Language Models (ICML 2025) [paper]
-
ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think (ICML 2025) [paper]
-
Understanding the Forgetting of (Replay-based) Continual Learning via Feature Learning: Angle Matters (ICML 2025) [paper]
-
Model Uncertainty Quantification by Conformal Prediction in Continual Learning (ICML 2025) [paper]
-
Learning without Isolation: Pathway Protection for Continual Learning (ICML 2025) [paper][code]
-
iDPA: Instance Decoupled Prompt Attention for Incremental Medical Object Detection (ICML 2025) [paper][code]
-
Online Curvature-Aware Replay: Leveraging $\mathbf{2^{nd}}$ Order Information for Online Continual Learning (ICML 2025) [paper]
-
CAN: Leveraging Clients As Navigators for Generative Replay in Federated Continual Learning (ICML 2025) [paper][code]
-
Adaptive Localization of Knowledge Negation for Continual LLM Unlearning (ICML 2025) [paper][code]
-
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models (ICML 2025) [paper][code]
-
FedSSI: Rehearsal-Free Continual Federated Learning with Synergistic Synaptic Intelligence (ICML 2025) [paper]
-
Semantic Shift Estimation via Dual-Projection and Classifier Reconstruction for Exemplar-Free Class-Incremental Learning (ICML 2025) [paper][code]
-
Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective (ICML 2025) [paper]
-
Where is the Truth? The Risk of Getting Confounded in a Continual World (ICML 2025) [paper][code]
-
Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning (ICML 2025) [paper][code]
-
Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian Perspective (ICML 2025) [paper][code]
-
Autoencoder-Based Hybrid Replay for Class-Incremental Learning (ICML 2025) [paper]
-
Probabilistic Group Mask Guided Discrete Optimization for Incremental Learning (ICML 2025) [paper][code]
-
Large Continual Instruction Assistant (ICML 2025) [paper][code]
-
TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree (ICML 2025) [paper]
-
Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting (ICML 2025) [paper]
-
Prototype-Based Continual Learning with Label-free Replay Buffer and Cluster Preservation Loss (CVPR Workshop 2025) [paper]
-
Prototype Augmented Hypernetworks for Continual Learning (CVPR Workshop 2025) [paper]
-
Language Guided Concept Bottleneck Models for Interpretable Continual Learning (CVPR 2025) [paper][code]
-
Dynamic Integration of Task-Specific Adapters for Class Incremental Learning (CVPR 2025) [paper]
-
Towards Continual Universal Segmentation (CVPR 2025) [paper]
-
Activating Sparse Part Concepts for 3D Class Incremental Learning (CVPR 2025) [paper][code]
-
Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot Manipulation (CVPR 2025) [paper]
-
CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning (CVPR 2025) [paper][code]
-
CoMBO: Conflict Mitigation via Branched Optimization for Class Incremental Segmentation (CVPR 2025) [paper][code]
-
BiLoRA: Almost-orthogonal Parameter Spaces for Continual Learning (CVPR 2025) [paper][code]
-
Attraction Diminishing and Distributing for Few-Shot Class-Incremental Learning (CVPR 2025) [paper]
-
Incremental Object Keypoint Learning (CVPR 2025) [paper]
-
Enhancing Online Continual Learning with Plug-and-Play State Space Model and Class-Conditional Mixture of Discretization (CVPR 2025) [paper][code]
-
AdaDARE-gamma: Balancing Stability and Plasticity in Multi-modal LLMs through Efficient Adaptation (CVPR 2025) [paper]
-
SEC-Prompt:SEmantic Complementary Prompting for Few-Shot Class-Incremental Learning (CVPR 2025) [paper]
-
Knowledge Memorization and Rumination for Pre-trained Model-based Class-Incremental Learning (CVPR 2025) [paper][code]
-
Advancing Multiple Instance Learning with Continual Learning for Whole Slide Imaging (CVPR 2025) [paper]
-
Revisiting Generative Replay for Class Incremental Object Detection (CVPR 2025) [paper][code]
-
Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning (CVPR 2025) [paper][code]
-
Online Task-Free Continual Learning via Dynamic Expansionable Memory Distribution (CVPR 2025) [paper][code]
-
H2ST: Hierarchical Two-Sample Tests for Continual Out-of-Distribution Detection (CVPR 2025) [paper][code]
-
KAC: Kolmogorov-Arnold Classifier for Continual Learning (CVPR 2025) [paper][code]
-
FALCON: Fairness Learning via Contrastive Attention Approach to Continual Semantic Scene Understanding (CVPR 2025) [paper]
-
Stacking Brick by Brick: Aligned Feature Isolation for Incremental Face Forgery Detection (CVPR 2025) [paper][code]
-
T-CIL: Temperature Scaling using Adversarial Perturbation for Calibration in Class-Incremental Learning (CVPR 2025) [paper]
-
LoRA Subtraction for Drift-Resistant Space in Exemplar-Free Continual Learning (CVPR 2025) [paper][code]
-
Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning (CVPR 2025) [paper]
-
Unsupervised Continual Domain Shift Learning with Multi-Prototype Modeling (CVPR 2025) [paper]
-
Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning (CVPR 2025) [paper][code]
-
Enhancing Few-Shot Class-Incremental Learning via Training-Free Bi-Level Modality Calibration (CVPR 2025) [paper][code]
-
Reducing Class-wise Confusion for Incremental Learning with Disentangled Manifolds (CVPR 2025) [paper][code]
-
ProtoDepth: Unsupervised Continual Depth Completion with Prototypes (CVPR 2025) [paper][code]
-
Beyond Background Shift: Rethinking Instance Replay in Continual Semantic Segmentation (CVPR 2025) [paper][code]
-
Do Your Best and Get Enough Rest for Continual Learning (CVPR 2025) [paper][code]
-
Task-Agnostic Guided Feature Expansion for Class-Incremental Learning (CVPR 2025) [paper][code]
-
ConceptGuard: Continual Personalized Text-to-Image Generation with Forgetting and Confusion Mitigation (CVPR 2025) [paper]
-
Synthetic Data is an Elegant GIFT for Continual Vision-Language Models (CVPR 2025) [paper][code]
-
Rethinking Query-based Transformer for Continual Image Segmentation (CVPR 2025) [paper][code]
-
Boosting Domain Incremental Learning: Selecting the Optimal Parameters is All You Need (CVPR 2025) [paper][code]
-
Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping (CVPR 2025) [paper][code]
-
Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental Learning (CVPR 2025) [paper][code]
-
AVQACL: A Novel Benchmark for Audio-Visual Question Answering Continual Learning (CVPR 2025) [paper][code]
-
Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor (CVPR 2025) [paper][code]
-
One-for-More: Continual Diffusion Model for Anomaly Detection (CVPR 2025) [paper][code]
-
Learning Conditional Space-Time Prompt Distributions for Video Class-Incremental Learning (CVPR 2025) [paper][code]
-
Adaptive Retention & Correction: Test-Time Training for Continual Learning (ICLR 2025) [paper][code]
-
Prototype antithesis for biological few-shot class-incremental learning (ICLR 2025) [paper]
-
Coreset Selection via Reducible Loss in Continual Learning (ICLR 2025) [paper][code]
-
LOIRE: LifelOng learning on Incremental data via pre-trained language model gRowth Efficiently (ICLR 2025) [paper]
-
Active Learning for Continual Learning: Keeping the Past Alive in the Present (ICLR 2025) [paper]
-
TSVD: Bridging Theory and Practice in Continual Learning with Pre-trained Models (ICLR 2025) [paper][code]
-
On Large Language Model Continual Unlearning (ICLR 2025) [paper][code]
-
SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning (ICLR 2025) [paper][code]
-
Federated Class-Incremental Learning: A Hybrid Approach Using Latent Exemplars and Data-Free Techniques to Address Local and Global Forgetting (ICLR 2025) [paper]
-
ADAPT: Attentive Self-Distillation and Dual-Decoder Prediction Fusion for Continual Panoptic Segmentation (ICLR 2025) [paper][code]
-
Semantic Aware Representation Learning for Lifelong Learning (ICLR 2025) [paper][code]
-
Spurious Forgetting in Continual Learning of Language Models (ICLR 2025) [paper][code]
-
CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained Models (ICLR 2025) [paper][code]
-
Theory on Mixture-of-Experts in Continual Learning (ICLR 2025) [paper]
-
Boosting Multiple Views for pretrained-based Continual Learning (ICLR 2025) [paper]
-
STAR: Stability-Inducing Weight Perturbation for Continual Learning (ICLR 2025) [paper][code]
-
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory (ICLR 2025) [paper]
-
Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification (ICLR 2025) [paper]
-
Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning (ICLR 2025) [paper][code]
-
A Second-Order Perspective on Model Compositionality and Incremental Learning (ICLR 2025) [paper][code]
-
C-CLIP: Multimodal Continual Learning for Vision-Language Model (ICLR 2025) [paper][code]
-
Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline (ICLR 2025) [paper][code]
-
Adapt-$\infty$: Scalable Continual Multimodal Instruction Tuning via Dynamic Data Selection (ICLR 2025) [paper][code]
-
Learning Continually by Spectral Regularization (ICLR 2025) [paper]
-
Self-Normalized Resets for Plasticity in Continual Learning (ICLR 2025) [paper][code]
-
PseDet: Revisiting the Power of Pseudo Label in Incremental Object Detection (ICLR 2025) [paper][code]
-
Meta-Continual Learning of Neural Fields (ICLR 2025) [paper][code]
-
Vision and Language Synergy for Rehearsal Free Continual Learning (ICLR 2025) [paper][code]
-
Advancing Prompt-based Methods for Replay-Independent General Continual Learning (ICLR 2025) [paper][code]
-
LoRA Subtraction for Drift-Resistant Space in Exemplar-Free Continual Learning (CVPR2025) [paper][code]
-
KAC: Kolmogorov-Arnold Classifier for Continual Learning (CVPR2025) [paper][code]
-
HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient Tuning (TPAMI 2025) [paper]
-
Adaptive Score Alignment Learning for Continual Perceptual Quality Assessment of 360-Degree Videos in Virtual Reality (VR-TVCG 2025) [paper][code]
2024
-
Mask and Compress: Efficient Skeleton-based Action Recognition in Continual Learning (ICPR2024) [paper][code]
-
CLIP with Generative Latent Replay: a Strong Baseline for Incremental Learning (BMVC24)[paper][code]
-
Learning a Low-Rank Feature Representation: Achieving Better Trade-Off between Stability and Plasticity in Continual Learning (ICASSP2024) [paper] [code]
-
Fine-Grained Knowledge Selection and Restoration for Non-Exemplar Class Incremental Learning (AAAI2024)[paper]
-
Maintaining Fairness in Logit-based Knowledge Distillation for Class-Incremental Learning (AAAI 2024) [paper][code]
-
Stabilizing Zero-Shot Prediction: A Novel Antidote to Forgetting in Continual Vision-Language Tasks (NeurIPS 2024) [paper][code]
-
GACL: Exemplar-Free Generalized Analytic Continual Learning (NeurIPS 2024) [paper][code]
-
Continual Audio-Visual Sound Separation (NeurIPS 2024) [paper][code]
-
F-OAL: Forward-only Online Analytic Learning with Fast Training and Low Memory Footprint in Class Incremental Learning (NeurIPS 2024) [paper][code]
-
Adaptive Visual Scene Understanding: Incremental Scene Graph Generation (NeurIPS 2024) [paper][code]
-
Task Confusion and Catastrophic Forgetting in Class-Incremental Learning: A Mathematical Framework for Discriminative and Generative Modelings (NeurIPS 2024) [paper]
-
Forgetting, Ignorance or Myopia: Revisiting Key Challenges in Online Continual Learning (NeurIPS 2024) [paper][code]
-
Continual Learning in the Frequency Domain (NeurIPS 2024) [paper][code]
-
Saliency-driven Experience Replay for Continual Learning (NeurIPS 2024) [paper][code]
-
PCoTTA: Continual Test-Time Adaptation for Multi-Task Point Cloud Understanding (NeurIPS 2024) [paper][code]
-
Advancing Cross-domain Discriminability in Continual Learning of Vision-Language Models (NeurIPS 2024) [paper][code]
-
Continual Learning with Global Alignment (NeurIPS 2024) [paper]
-
Disentangling and mitigating the impact of task similarity for continual learning (NeurIPS 2024) [paper]
-
Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach (NeurIPS 2024) [paper][code]
-
Make Continual Learning Stronger via C-Flat (NeurIPS 2024) [paper][code]
-
ViLCo-Bench: VIdeo Language COntinual learning Benchmark (NeurIPS 2024) [paper][code]
-
Not Just Object, But State: Compositional Incremental Learning without Forgetting (NeurIPS 2024) [paper][code]
-
Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning (NeurIPS 2024) [paper][code]
-
Random Representations Outperform Online Continually Learned Representations (NeurIPS 2024) [paper][code]
-
Mixture of Experts Meets Prompt-Based Continual Learning (NeurIPS 2024) [paper][code]
-
SAFE: Slow and Fast Parameter-Efficient Tuning for Continual Learning with Pre-Trained Models (NeurIPS 2024) [paper][code]
-
Train-Attention: Meta-Learning Where to Focus in Continual Knowledge Learning (NeurIPS 2024) [paper][code]
-
Persistence Homology Distillation for Semi-supervised Continual Learning (NeurIPS 2024) [paper][code]
-
Continual learning with the neural tangent ensemble (NeurIPS 2024) [paper]
-
Vector Quantization Prompting for Continual Learning (NeurIPS 2024) [paper][code]
-
CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models (NeurIPS 2024) [paper][code]
-
An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning (NeurIPS 2024) [paper][code]
-
Label Delay in Online Continual Learning (NeurIPS 2024) [paper][code]
-
Visual Prompt Tuning in Null Space for Continual Learning (NeurIPS 2024) [paper][code]
-
Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation (NeurIPS 2024) [paper]
-
A Topology-aware Graph Coarsening Framework for Continual Graph Learning (NeurIPS 2024) [paper][code]
-
What Matters in Graph Class Incremental Learning? An Information Preservation Perspective (NeurIPS 2024) [paper][code]
-
Happy: A Debiased Learning Framework for Continual Generalized Category Discovery (NeurIPS 2024) [paper][code]
-
MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment (ECCV 2024) [paper][code]
-
Early Preparation Pays Off: New Classifier Pre-tuning for Class Incremental Semantic Segmentation (ECCV24)[paper][code]
-
Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion (ECCV24)[paper][code]
-
Bridge Past and Future: Overcoming Information Asymmetry in Incremental Object Detection (ECCV24)[paper][code]
-
Confidence Self-Calibration for Multi-Label Class-Incremental Learning (ECCV24)[paper]
-
Rethinking Few-shot Class-incremental Learning: Learning from Yourself (ECCV24)[paper][code]
-
Versatile Incremental Learning: Towards Class and Domain-Agnostic Incremental Learning (ECCV24)[paper][code]
-
Scene Coordinate Reconstruction: Posing of Image Collections via Incremental Learning of a Relocalizer (ECCV24)[paper][code]
-
Mitigating Background Shift in Class-Incremental Semantic Segmentation (ECCV24)[paper][code]
-
Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching (ECCV24)[paper]
-
Learning from the Web: Language Drives Weakly-Supervised Incremental Learning for Semantic Segmentation (ECCV24)[paper][code]
-
Tendency-driven Mutual Exclusivity for Weakly Supervised Incremental Semantic Segmentation (ECCV24)[paper]
-
Cs2K: Class-specific and Class-shared Knowledge Guidance for Incremental Semantic Segmentation (ECCV24)[paper]
-
DiffClass: Diffusion-Based Class Incremental Learning (ECCV24)[paper][code]
-
PILoRA: Prototype Guided Incremental LoRA for Federated Class-Incremental Learning (ECCV24)[paper][code]
-
Few-shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt (ECCV24)[paper][code]
-
iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning (ECCV24)[paper][code]
-
Background Adaptation with Residual Modeling for Exemplar-Free Class-Incremental Semantic Segmentation (ECCV24)[paper][code]
-
Continual Learning for Remote Physiological Measurement: Minimize Forgetting and Simplify Inference (ECCV24)[paper][code]
-
Semantic Residual Prompts for Continual Learning (ECCV24)[paper][code]
-
Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery (ECCV24)[paper][code]
-
CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning (ECCV24)[paper][code]
-
Beyond Prompt Learning: Continual Adapter for Efficient Rehearsal-Free Continual Learning (ECCV24)[paper]
-
Mind the Interference: Retaining Pre-trained Knowledge in Parameter Efficient Continual Learning of Vision-Language Models (ECCV24)[paper][code]
-
Reshaping the Online Data Buffering and Organizing Mechanism for Continual Test-Time Adaptation (ECCV24)[paper][code]
-
Revisiting Supervision for Continual Representation Learning (ECCV24)[paper][code]
-
Select and Distill: Selective Dual-Teacher Knowledge Transfer for Continual Learning on Vision-Language Models (ECCV24)[paper][code]
-
PromptFusion: Decoupling Stability and Plasticity for Continual Learning (ECCV24)[paper][code]
-
One-stage Prompt-based Continual Learning (ECCV24)[paper]
-
Preventing Catastrophic Forgetting through Memory Networks in Continuous Detection (ECCV24)[paper][code]
-
Exemplar-free Continual Representation Learning via Learnable Drift Compensation (ECCV24)[paper][code]
-
Open-World Dynamic Prompt and Continual Visual Representation Learning (ECCV24)[paper]
-
Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning (ECCV24)[paper][code]
-
PromptCCD: Learning Gaussian Mixture Prompt Pool for Continual Category Discovery (ECCV24)[paper][code]
-
MagMax: Leveraging Model Merging for Seamless Continual Learning (ECCV24)[paper][code]
-
Anytime Continual Learning for Open Vocabulary Classification (ECCV24)[paper][code]
-
Weighted Ensemble Models Are Strong Continual Learners (ECCV24)[paper][code]
-
CLEO: Continual Learning of Evolving Ontologies (ECCV24)[paper][code]
-
UNIKD: UNcertainty-Filtered Incremental Knowledge Distillation for Neural Implicit Representation (ECCV24)[paper][code]
-
Canonical Shape Projection is All You Need for 3D Few-shot Class Incremental Learning (ECCV24)[paper][code]
-
STSP: Spatial-Temporal Subspace Projection for Video Class-incremental Learning (ECCV24)[paper]
-
Non-Exemplar Domain Incremental Learning via Cross-Domain Concept Integration (ECCV24)[paper]
-
CLOSER: Towards Better Representation Learning for Few-Shot Class-Incremental Learning (ECCV24)[paper][code]
-
On the Approximation Risk of Few-Shot Class-Incremental Learning (ECCV24)[paper][code]
-
Adapt without Forgetting: Distill Proximity from Dual Teachers in Vision-Language Models (ECCV24)[paper][code]
-
Information Bottleneck Based Data Correction in Continual Learning (ECCV24)[paper]
-
Continual Learning and Unknown Object Discovery in 3D Scenes via Self-Distillation (ECCV24)[paper][code]
-
Pick-a-back: Selective Device-to-Device Knowledge Transfer in Federated Continual Learning (ECCV24)[paper][code]
-
Human Motion Forecasting in Dynamic Domain Shifts: A Homeostatic Continual Test-time Adaptation Framework (ECCV24)[paper]
-
CLIFF: Continual Latent Diffusion for Open-Vocabulary Object Detection (ECCV24)[paper][code]
-
RCS-Prompt: Learning Prompt to Rearrange Class Space for Prompt-based Continual Learning (ECCV24)[paper][code]
-
Online Continuous Generalized Category Discovery (ECCV24)[paper][code]
-
Class-incremental Learning for Time Series: Benchmark and Evaluation (KDD24)[paper][code]
-
Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning (ICML24)[paper]
-
Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning (ICML24)[paper][code]
-
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning (ICML24)[paper]
-
Learning to Continually Learn with the Bayesian Principle (ICML24)[paper][code]
-
Rethinking Momentum Knowledge Distillation in Online Continual Learning (ICML24)[paper][code]
-
Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning (ICML24)[paper]
-
Bayesian Adaptation of Network Depth and Width for Continual Learning (ICML24)[paper]
-
STELLA: Continual Audio-Video Pre-training with SpatioTemporal Localized Alignment (ICML24)[paper][code]
-
On the Diminishing Returns of Width for Continual Learning (ICML24)[paper][code]
-
Compositional Few-Shot Class-Incremental Learning (ICML24)[paper][code]
-
Rapid Learning without Catastrophic Forgetting in the Morris Water Maze (ICML24)[paper][code]
-
Understanding Forgetting in Continual Learning with Linear Regression (ICML24)[paper]
-
Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization (ICML24)[paper]
-
Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning (ICML24)[paper]
-
Provable Contrastive Continual Learning (ICML24)[paper]
-
Gradual Divergence for Seamless Adaptation: A Novel Domain Incremental Learning Method (ICML24)[paper][code]
-
An Effective Dynamic Gradient Calibration Method for Continual Learning (ICML24)[paper]
-
Federated Continual Learning via Prompt-based Dual Knowledge Transfer (ICML24)[paper][code]
-
COPAL: Continual Pruning in Large Language Generative Models (ICML24)[paper]
-
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning (ICML24)[paper]
-
Hierarchical Augmentation and Distillation for Class Incremental Audio-Visual Video Recognition (TPAMI2024)[paper]
-
- DELTA: Decoupling Long-Tailed Online Continual Learning (CVPR Workshop 2024)[paper][Code]
-
AIDE: An Automatic Data Engine for Object Detection in Autonomous Driving (CVPR2024)[paper]
-
Continual Segmentation with Disentangled Objectness Learning and Class Recognition (CVPR2024)[paper][code]
-
Interactive Continual Learning: Fast and Slow Thinking (CVPR2024)[paper][code]
-
InfLoRA: Interference-Free Low-Rank Adaptation for Continual Learning (CVPR2024)[paper][code]
-
Semantically-Shifted Incremental Adapter-Tuning is A Continual ViTransformer (CVPR2024)[paper][code]
-
Traceable Federated Continual Learning (CVPR2024)[paper][code]
-
Defense without Forgetting: Continual Adversarial Defense with Anisotropic & Isotropic Pseudo Replay (CVPR2024)[paper]
-
Learning Continual Compatible Representation for Re-indexing Free Lifelong Person Re-identification (CVPR2024)[paper][code]
-
Towards Backward-Compatible Continual Learning of Image Compression (CVPR2024)[paper][code]
-
Class Incremental Learning with Multi-Teacher Distillation (CVPR2024)[paper][code]
-
Towards Efficient Replay in Federated Incremental Learning (CVPR2024)[paper]
-
Dual-consistency Model Inversion for Non-exemplar Class Incremental Learning (CVPR2024)[paper]
-
Dual-Enhanced Coreset Selection with Class-wise Collaboration for Online Blurry Class Incremental Learning (CVPR2024)[paper]
-
Coherent Temporal Synthesis for Incremental Action Segmentation (CVPR2024)[paper]
-
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning (CVPR2024)[paper][code]
-
NICE: Neurogenesis Inspired Contextual Encoding for Replay-free Class Incremental Learning (CVPR2024)[paper][code]
-
Long-Tail Class Incremental Learning via Independent Sub-prototype Construction (CVPR2024)[paper]
-
FCS: Feature Calibration and Separation for Non-Exemplar Class Incremental Learning (CVPR2024)[paper][code]
-
Incremental Nuclei Segmentation from Histopathological Images via Future-class Awareness and Compatibility-inspired Distillation (CVPR2024)[paper][code]
-
Gradient Reweighting: Towards Imbalanced Class-Incremental Learning (CVPR2024)[paper][code]
-
OrCo: Towards Better Generalization via Orthogonality and Contrast for Few-Shot Class-Incremental Learning (CVPR2024)[paper][code]
-
SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection (CVPR2024)[paper]
-
Generative Multi-modal Models are Good Class Incremental Learners (CVPR2024)[paper][code]
-
Task-Adaptive Saliency Guidance for Exemplar-free Class Incremental Learning (CVPR2024)[paper][code]
-
DYSON: Dynamic Feature Space Self-Organization for Online Task-Free Class Incremental Learning (CVPR2024)[paper][code]
-
Enhancing Visual Continual Learning with Language-Guided Supervision (CVPR2024)[paper]
-
Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters (CVPR2024)[paper][code]
-
Adaptive VIO: Deep Visual-Inertial Odometry with Online Continual Learning (CVPR2024)[paper]
-
Continual Self-supervised Learning: Towards Universal Multi-modal Medical Data Representation Learning (CVPR2024)[paper][code]
-
ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt Tuning (CVPR2024)[paper][code]
-
Online Task-Free Continual Generative and Discriminative Learning via Dynamic Cluster Memory (CVPR2024)[paper][code]
-
Learning from One Continuous Video Stream (CVPR2024)[paper]
-
Improving Plasticity in Online Continual Learning via Collaborative Learning (CVPR2024)[paper][code]
-
Learning Equi-angular Representations for Online Continual Learning (CVPR2024)[paper][code]
-
BrainWash: A Poisoning Attack to Forget in Continual Learning (CVPR2024)[paper]
-
Consistent Prompting for Rehearsal-Free Continual Learning (CVPR2024)[paper][code]
-
Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning (CVPR2024)[paper][code]
-
Convolutional Prompting meets Language Models for Continual Learning (CVPR2024)[paper][code]
-
Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning (CVPR2024)[paper][code]
-
Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners (CVPR2024)[paper][code]
-
Orchestrate Latent Expertise: Advancing Online Continual Learning with Multi-Level Supervision and Reverse Self-Distillation (CVPR2024)[paper][code]
-
Elastic Feature Consolidation For Cold Start Exemplar-Free Incremental Learning (ICLR2024)[paper][code]
-
Function-space Parameterization of Neural Networks for Sequential Learning (ICLR2024)[paper]
-
Progressive Fourier Neural Representation for Sequential Video Compilation (ICLR2024)[paper]
-
Kalman Filter Online Classification from non-Stationary Data (ICLR2024)[paper]
-
Continual Momentum Filtering on Parameter Space for Online Test-time Adaptation (ICLR2024)[paper]
-
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models (ICLR2024)[paper]
-
Class Incremental Learning via Likelihood Ratio Based Task Prediction (ICLR2024)[paper][code]
-
The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting - An Analytical Model (ICLR2024)[paper]
-
Prediction Error-based Classification for Class-Incremental Learning (ICLR2024)[paper][code]
-
Adapting Large Language Models via Reading Comprehension (ICLR2024)[paper][code]
-
Accurate Forgetting for Heterogeneous Federated Continual Learning (ICLR2024)[paper]
-
Fixed Non-negative Orthogonal Classifier: Inducing Zero-mean Neural Collapse with Feature Dimension Separation (ICLR2024)[paper]
-
A Probabilistic Framework for Modular Continual Learning (ICLR2024)[paper]
-
A Unified and General Framework for Continual Learning (ICLR2024)[paper]
-
Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation (ICLR2024)[paper]
-
CPPO: Continual Learning for Reinforcement Learning with Human Feedback (ICLR2024)[paper]
-
Online Continual Learning for Interactive Instruction Following Agents (ICLR2024)[paper][code]
-
Scalable Language Model with Generalized Continual Learning (ICLR2024)[paper]
-
ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation (ICLR2024)[paper]
-
Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks (ICLR2024)[paper][code]
-
TiC-CLIP: Continual Training of CLIP Models (ICLR2024)[paper]
-
Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline (ICLR2024)[paper]
-
Addressing Catastrophic Forgetting and Loss of Plasticity in Neural Networks (ICLR2024)[paper]
-
Locality Sensitive Sparse Encoding for Learning World Models Online (ICLR2024)[paper]
-
Dissecting learning and forgetting in language model finetuning (ICLR2024)[paper]
-
Prompt Gradient Projection for Continual Learning (ICLR2024)[paper][code]
-
Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time (ICLR2024)[paper]
-
Divide and not forget: Ensemble of selectively trained experts in Continual Learning (ICLR2024)[paper][code]
-
eTag: Class-Incremental Learning via Embedding Distillation and Task-Oriented Generation (AAAI2024) [paper][code]
-
Evolving Parameterized Prompt Memory for Continual Learning (AAAI2024)[paper][code]
-
Towards Continual Learning Desiderata via HSIC-Bottleneck Orthogonalization and Equiangular Embedding (AAAI2024)[paper]
-
Fine-Grained Knowledge Selection and Restoration for Non-Exemplar Class Incremental Learning (AAAI2024)[paper]
-
Class-Incremental Learning: Cross-Class Feature Augmentation for Class Incremental Learning (AAAI2024)[paper]
-
Learning Task-Aware Language-Image Representation for Class-Incremental Object Detection (AAAI2024)[paper]
-
MIND: Multi-Task Incremental Network Distillation (AAAI2024)[paper][code]
-
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning (WACV2024)[paper][code]
-
Plasticity-Optimized Complementary Networks for Unsupervised Continual (WACV2024)[paper]
-
Online Class-Incremental Learning For Real-World Food Image Classification (WACV2024)[paper]
2023
- RaSP: Relation-aware Semantic Prior for Weakly Supervised Incremental Segmentation (CoLLAs 2023) [paper] [code]
- SIESTA: Efficient Online Continual Learning with Sleep (TMLR 2023)[paper]
- Sub-network Discovery and Soft-masking for Continual Learning of Mixed Tasks (EMNLP 2023)[paper]
- Incorporating neuro-inspired adaptability for continual learning in artificial intelligence (Nature Machine Intelligence 2023) [paper]
- Enhancing Knowledge Transfer for Task Incremental Learning with Data-free Subnetwork (NeurIPS 2023) [paper] [Code]
- Loss Decoupling for Task-Agnostic Continual Learning (NeurIPS 2023) [paper]
- Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm (NeurIPS 2023)[paper]
- Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments (NeurIPS 2023)[paper]
- An Efficient Dataset Condensation Plugin and Its Application to Continual Learning (NeurIPS 2023)[paper]
- Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation (NeurIPS 2023)[paper]
- Prediction and Control in Continual Reinforcement Learning (NeurIPS 2023)[paper]
- On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm (NeurIPS 2023)[paper]
- Saving 100x Storage: Prototype Replay for Reconstructing Training Sample Distribution in Class-Incremental Semantic Segmentation (NeurIPS 2023)[paper]
- A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks (NeurIPS 2023)[paper]
- Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration (NeurIPS 2023)[paper]
- A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm (NeurIPS 2023)[paper][code]
- Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees (NeurIPS 2023)[paper][code]
- Recasting Continual Learning as Sequence Modeling (NeurIPS 2023)[paper]
- Augmented Memory Replay-based Continual Learning Approaches for Network Intrusion Detection (NeurIPS 2023)[paper]
- Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework (NeurIPS 2023)[paper]
- CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation (NeurIPS 2023)[paper]
- TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion (NeurIPS 2023)[paper]
- Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models (NeurIPS 2023)[paper]
- A Definition of Continual Reinforcement Learning (NeurIPS 2023)[paper]
- RanPAC: Random Projections and Pre-trained Models for Continual Learning (NeurIPS 2023)[paper]
- Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality (NeurIPS 2023)[paper]
- FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning (NeurIPS 2023)[paper]
- The Ideal Continual Learner: An Agent That Never Forgets (ICML2023) [paper]
- Continual Learners are Incremental Model Generalizers (ICML2023)[paper]
- Learnability and Algorithm for Continual Learning (ICML2023)[paper][code]
- Parameter-Level Soft-Masking for Continual Learning (ICML2023)[paper]
- Continual Learning in Linear Classification on Separable Data (ICML2023)[paper]
- DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning (ICML2023)[paper]
- BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning (ICML2023)[paper]
- DDGR: Continual Learning with Deep Diffusion-based Generative Replay (ICML2023)[paper]
- Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal (ICML2023)[paper]
- Theory on Forgetting and Generalization of Continual Learning (ICML2023)[paper]
- Poisoning Generative Replay in Continual Learning to Promote Forgetting (ICML2023)[paper]
- Continual Vision-Language Representation Learning with Off-Diagonal Information (ICML2023)[paper]
- Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning (ICML2023)[paper]
- Does Continual Learning Equally Forget All Parameters? (ICML2023)[paper]
- Growing a Brain with Sparsity-Inducing Generation for Continual Learning (ICCV 2023)[paper][code]
- Self-regulating Prompts: Foundational Model Adaptation without Forgetting (ICCV 2023)[paper][code]
- Prototype Reminiscence and Augmented Asymmetric Knowledge Aggregation for Non-Exemplar Class-Incremental Learning (ICCV 2023)[paper][code]
- Tangent Model Composition for Ensembling and Continual Fine-tuning (ICCV 2023)[paper][code]
- CBA: Improving Online Continual Learning via Continual Bias Adaptor (ICCV 2023)[paper]
- CTP: Towards Vision-Language Continual Pretraining via Compatible Momentum Contrast and Topology Preservation (ICCV 2023)[paper][code]
- NAPA-VQ: Neighborhood Aware Prototype Augmentation with Vector Quantization for Continual Learning (ICCV 2023)[paper][code]
- Online Continual Learning on Hierarchical Label Expansion (ICCV 2023)[paper]
- Class-Incremental Grouping Network for Continual Audio-Visual Learning (ICCV 2023)[paper][code]
- Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right? (ICCV 2023)[paper][code]
- When Prompt-based Incremental Learning Does Not Meet Strong Pretraining (ICCV 2023)[paper]
- Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning (ICCV 2023)[paper][code]
- Dynamic Residual Classifier for Class Incremental Learning (ICCV 2023)[paper]
- First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental Learning (ICCV 2023)[paper]
- Masked Autoencoders are Efficient Class Incremental Learners (ICCV 2023)[paper]
- Introducing Language Guidance in Prompt-based Continual Learning (ICCV 2023)[paper]
- CLNeRF: Continual Learning Meets NeRFs (ICCV 2023)[paper]
- Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models (ICCV 2023)[paper][code]
- LFS-GAN: Lifelong Few-Shot Image Generation (ICCV 2023)[paper]
- TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation (ICCV 2023)[paper]
- Learning to Learn: How to Continuously Teach Humans and Machines (ICCV 2023)[paper]
- Audio-Visual Class-Incremental Learning (ICCV 2023)[paper][code]
- MetaGCD: Learning to Continually Learn in Generalized Category Discovery (ICCV 2023)[paper]
- Exemplar-Free Continual Transformer with Convolutions (ICCV 2023)[paper][code]
- A Unified Continual Learning Framework with General Parameter-Efficient Tuning (ICCV 2023)[paper]
- Incremental Generalized Category Discovery (ICCV 2023)[paper]
- Heterogeneous Forgetting Compensation for Class-Incremental Learning (ICCV 2023)[paper][code]
- Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection (ICCV 2023)[paper][code]
- MRN: Multiplexed Routing Network for Incremental Multilingual Text Recognition (ICCV 2023)[paper][code]
- CLR: Channel-wise Lightweight Reprogramming for Continual Learning (ICCV 2023)[paper][code]
- ICICLE: Interpretable Class Incremental Continual Learning (ICCV 2023)[paper]
- Proxy Anchor-based Unsupervised Learning for Continuous Generalized Category Discovery (ICCV 2023)[paper]
- SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model (ICCV 2023)[paper][code]
- Online Prototype Learning for Online Continual Learning (ICCV 2023)[paper][code]
- Analyzing and Reducing the Performance Gap in Cross-Lingual Transfer with Fine-tuning Slow and Fast (ACL2023)[paper]
- Class-Incremental Learning based on Label Generation (ACL2023)[paper]
- Computationally Budgeted Continual Learning: What Does Matter? (CVPR2023)[paper][code]
- Real-Time Evaluation in Online Continual Learning: A New Hope (CVPR2023)[paper]
- Dealing With Cross-Task Class Discrimination in Online Continual Learning (CVPR2023)[paper][code]
- Decoupling Learning and Remembering: A Bilevel Memory Framework With Knowledge Projection for Task-Incremental Learning (CVPR2023)[paper][code]
- GKEAL: Gaussian Kernel Embedded Analytic Learning for Few-shot Class Incremental Task (CVPR2023)[paper]
- EcoTTA: Memory-Efficient Continual Test-time Adaptation via Self-distilled Regularization (CVPR2023)[paper]
- Endpoints Weight Fusion for Class Incremental Semantic Segmentation (CVPR2023)[paper]
- On the Stability-Plasticity Dilemma of Class-Incremental Learning (CVPR2023)[paper]
- Regularizing Second-Order Influences for Continual Learning (CVPR2023)[paper][code]
- Rebalancing Batch Normalization for Exemplar-based Class-Incremental Learning (CVPR2023)[paper]
- Task Difficulty Aware Parameter Allocation & Regularization for Lifelong Learning (CVPR2023)[paper]
- A Probabilistic Framework for Lifelong Test-Time Adaptation (CVPR2023)[paper][code]
- Continual Semantic Segmentation with Automatic Memory Sample Selection (CVPR2023)[paper]
- Exploring Data Geometry for Continual Learning (CVPR2023)[paper]
- PCR: Proxy-based Contrastive Replay for Online Class-Incremental Continual Learning (CVPR2023)[paper][code]
- Learning with Fantasy: Semantic-Aware Virtual Contrastive Constraint for Few-Shot Class-Incremental Learning (CVPR2023)[paper][code]
- Foundation Model Drives Weakly Incremental Learning for Semantic Segmentation (CVPR2023)[paper]
- Continual Detection Transformer for Incremental Object Detection (CVPR2023)[paper][code]
- PIVOT: Prompting for Video Continual Learning (CVPR2023)[paper]
- CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning (CVPR2023)[paper][code]
- Principles of Forgetting in Domain-Incremental Semantic Segmentation in Adverse Weather Conditions (CVPR2023)[paper]
- Class-Incremental Exemplar Compression for Class-Incremental Learning (CVPR2023)[paper][code]
- Dense Network Expansion for Class Incremental Learning (CVPR2023)[paper]
- Online Bias Correction for Task-Free Continual Learning (ICLR2023)[paper]
- Sparse Distributed Memory is a Continual Learner (ICLR2023)[paper]
- Continual Learning of Language Models (ICLR2023)[paper]
- Progressive Prompts: Continual Learning for Language Models without Forgetting (ICLR2023)[paper]
- Is Forgetting Less a Good Inductive Bias for Forward Transfer? (ICLR2023)[paper]
- Online Boundary-Free Continual Learning by Scheduled Data Prior (ICLR2023)[paper]
- Incremental Learning of Structured Memory via Closed-Loop Transcription (ICLR2023)[paper]
- Better Generative Replay for Continual Federated Learning (ICLR2023)[paper]
- 3EF: Class-Incremental Learning via Efficient Energy-Based Expansion and Fusion (ICLR2023)[paper]
- Progressive Voronoi Diagram Subdivision Enables Accurate Data-free Class-Incremental Learning (ICLR2023)[paper]
- Learning without Prejudices: Continual Unbiased Learning via Benign and Malignant Forgetting (ICLR2023)[paper]
- Building a Subspace of Policies for Scalable Continual Learning (ICLR2023)[paper]
- A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning (ICLR2023)[paper]
- Continual evaluation for lifelong learning: Identifying the stability gap (ICLR2023)[paper]
- Continual Unsupervised Disentangling of Self-Organizing Representations (ICLR2023)[paper]
- Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning (ICLR2023)[paper]
- Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning (ICLR2023)[paper]
- On the Soft-Subnetwork for Few-Shot Class Incremental Learning (ICLR2023)[paper]
- Task-Aware Information Routing from Common Representation Space in Lifelong Learning (ICLR2023)[paper]
- Error Sensitivity Modulation based Experience Replay: Mitigating Abrupt Representation Drift in Continual Learning (ICLR2023)[paper]
- Neural Weight Search for Scalable Task Incremental Learning (WACV2023)[paper]
- Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation (WACV2023)[paper]
- FeTrIL: Feature Translation for Exemplar-Free Class-Incremental Learning (WACV2023)[paper]
- Do Pre-trained Models Benefit Equally in Continual Learning? (WACV2023)[paper] [code]
- Sparse Coding in a Dual Memory System for Lifelong Learning (AAAI2023)[paper] [code]
2022
-
Online Continual Learning through Mutual Information Maximization (ICML2022)[paper]
-
Prototype-guided continual adaptation for class-incremental unsupervised domain adaptation (ECCV2022)[paper] [code]
-
Balanced softmax cross-entropy for incremental learning with and without memory (CVIU)[paper]
-
Incremental Prompting: Episodic Memory Prompt for Lifelong Event Detection (COLING2022) [paper] [code]
-
Improving Task-free Continual Learning by Distributionally Robust Memory Evolution (ICML2022)[paper]
-
Forget-free Continual Learning with Winning Subnetworks (ICML2022)[paper]
-
NISPA: Neuro-Inspired Stability-Plasticity Adaptation for Continual Learning in Sparse Networks (ICML2022)[paper]
-
Continual Learning via Sequential Function-Space Variational Inference (ICML2022)[paper]
-
A Theoretical Study on Solving Continual Learning (NeurIPS2022) [paper] [code]
-
ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection (NeurIPS2022) [paper]
-
Beyond Not-Forgetting: Continual Learning with Backward Knowledge Transfer (NeurIPS2022) [paper]
-
Memory Efficient Continual Learning with Transformers (NeurIPS2022) [paper]
-
Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting Mitigation (NeurIPS2022) [paper] [code]
-
Disentangling Transfer in Continual Reinforcement Learning (NeurIPS2022) [paper]
-
Task-Free Continual Learning via Online Discrepancy Distance Learning (NeurIPS2022) [paper]
-
A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal (NeurIPS2022) [paper]
-
S-Prompts Learning with Pre-trained Transformers: An Occam’s Razor for Domain Incremental Learning (NeurIPS2022) [paper]
-
Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting (NeurIPS2022) [paper]
-
Few-Shot Continual Active Learning by a Robot (NeurIPS2022) [paper]
-
Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions(NeurIPS2022) [paper]
-
SparCL: Sparse Continual Learning on the Edge(NeurIPS2022) [paper]
-
CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks (NeurIPS2022) [paper] [code]
-
Continual Learning In Environments With Polynomial Mixing Times (NeurIPS2022) [paper] [code]
-
Exploring Example Influence in Continual Learning (NeurIPS2022) [paper] [code]
-
ALIFE: Adaptive Logit Regularizer and Feature Replay for Incremental Semantic Segmentation (NeurIPS2022) [paper]
-
On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning (NeurIPS2022) [paper] [code]
-
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting (NeurIPS2022)[paper]
-
CGLB: Benchmark Tasks for Continual Graph Learning (NeurIPS2022)[paper] [code]
-
How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning? (NeurIPS2022)[paper]
-
CoSCL: Cooperation of Small Continual Learners is Stronger than a Big One (ECCV2022)[paper] [code]
-
Generative Negative Text Replay for Continual Vision-Language Pretraining (ECCV2022) [paper]
-
DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning (ECCV2022) [paper] [code]
-
The Challenges of Continuous Self-Supervised Learning (ECCV2022)[paper]
-
Helpful or Harmful: Inter-Task Association in Continual Learning (ECCV2022)[paper]
-
incDFM: Incremental Deep Feature Modeling for Continual Novelty Detection (ECCV2022)[paper]
-
S3C: Self-Supervised Stochastic Classifiers for Few-Shot Class-Incremental Learning (ECCV2022)[paper]
-
Online Task-free Continual Learning with Dynamic Sparse Distributed Memory (ECCV2022)[paper][code]
-
Balancing between Forgetting and Acquisition in Incremental Subpopulation Learning (ECCV2022)[paper]
-
Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer (ECCV2022) [paper] [code]
-
FOSTER: Feature Boosting and Compression for Class-Incremental Learning (ECCV2022) [paper] [code]
-
Meta-Learning with Less Forgetting on Large-Scale Non-Stationary Task Distributions (ECCV2022) [paper]
-
R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental Learning (ECCV2022) [paper] [code]
-
DLCFT: Deep Linear Continual Fine-Tuning for General Incremental Learning (ECCV2022) [paper]
-
Learning with Recoverable Forgetting (ECCV2022) [paper]
-
Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation (ECCV2022) [paper] [code]
-
Balancing Stability and Plasticity through Advanced Null Space in Continual Learning (ECCV2022) [paper]
-
Long-Tailed Class Incremental Learning (ECCV2022) [paper]
-
Anti-Retroactive Interference for Lifelong Learning (ECCV2022) [paper]
-
Novel Class Discovery without Forgetting (ECCV2022) [paper]
-
Class-incremental Novel Class Discovery (ECCV2022) [paper]
-
Few-Shot Class Incremental Learning From an Open-Set Perspective(ECCV2022)[paper]
-
Incremental Task Learning with Incremental Rank Updates(ECCV2022)[paper]
-
Few-Shot Class-Incremental Learning via Entropy-Regularized Data-Free Replay(ECCV2022)[paper]
-
Online Continual Learning with Contrastive Vision Transformer (ECCV2022)[paper]
-
Transfer without Forgetting (ECCV2022) [paper][code]
-
Continual Training of Language Models for Few-Shot Learning (EMNLP2022) [paper] [code]
-
Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation (TPAMI2022) [paper]
-
MgSvF: Multi-Grained Slow vs. Fast Framework for Few-Shot Class-Incremental Learning (TPAMI2022) [paper]
-
Class-Incremental Continual Learning into the eXtended DER-verse (TPAMI2022) [paper] [code]
-
Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks (TPAMI2022) [paper] [code]
-
Continual Semi-Supervised Learning through Contrastive Interpolation Consistency (PRL2022) [paper][code]
-
GCR: Gradient Coreset Based Replay Buffer Selection for Continual Learning (CVPR2022) [paper]
-
Learning Bayesian Sparse Networks With Full Experience Replay for Continual Learning (CVPR2022) [paper]
-
Continual Learning With Lifelong Vision Transformer (CVPR2022) [paper]
-
Towards Better Plasticity-Stability Trade-Off in Incremental Learning: A Simple Linear Connector (CVPR2022) [paper]
-
Doodle It Yourself: Class Incremental Learning by Drawing a Few Sketches (CVPR2022) [paper]
-
Continual Learning for Visual Search with Backward Consistent Feature Embedding (CVPR2022) [paper]
-
Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries (CVPR2022) [paper]
-
Not Just Selection, but Exploration: Online Class-Incremental Continual Learning via Dual View Consistency (CVPR2022) [paper]
-
Bring Evanescent Representations to Life in Lifelong Class Incremental Learning (CVPR2022) [paper]
-
Lifelong Graph Learning (CVPR2022) [paper]
-
Lifelong Unsupervised Domain Adaptive Person Re-identification with Coordinated Anti-forgetting and Adaptation (CVPR2022) [paper]
-
vCLIMB: A Novel Video Class Incremental Learning Benchmark (CVPR2022) [paper]
-
Class-Incremental Learning by Knowledge Distillation with Adaptive Feature Consolidation(CVPR2022) [paper]
-
Few-Shot Incremental Learning for Label-to-Image Translation (CVPR2022) [paper]
-
MetaFSCIL: A Meta-Learning Approach for Few-Shot Class Incremental Learning (CVPR2022) [paper]
-
Incremental Learning in Semantic Segmentation from Image Labels (CVPR2022) [paper]
-
Self-Supervised Models are Continual Learners (CVPR2022) [paper] [code]
-
Learning to Imagine: Diversify Memory for Incremental Learning using Unlabeled Data (CVPR2022) [paper]
-
General Incremental Learning with Domain-aware Categorical Representations (CVPR2022) [paper]
-
Constrained Few-shot Class-incremental Learning (CVPR2022) [paper]
-
Overcoming Catastrophic Forgetting in Incremental Object Detection via Elastic Response Distillation (CVPR2022) [paper]
-
Class-Incremental Learning with Strong Pre-trained Models (CVPR2022) [paper]
-
Energy-based Latent Aligner for Incremental Learning (CVPR2022) [paper] [code]
-
Meta-attention for ViT-backed Continual Learning (CVPR2022) [paper] [code]
-
Learning to Prompt for Continual Learning (CVPR2022) [paper] [code]
-
On Generalizing Beyond Domains in Cross-Domain Continual Learning (CVPR2022) [paper]
-
Probing Representation Forgetting in Supervised and Unsupervised Continual Learning (CVPR2022) [paper]
-
Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding (CVPR2022) [paper] [code]
-
Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning (CVPR2022) [paper] [code]
-
Forward Compatible Few-Shot Class-Incremental Learning (CVPR2022) [paper] [code]
-
Self-Sustaining Representation Expansion for Non-Exemplar Class-Incremental Learning (CVPR2022) [paper]
-
DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion (CVPR2022) [paper]
-
Federated Class-Incremental Learning (CVPR2022) [paper] [code]
-
Representation Compensation Networks for Continual Semantic Segmentation (CVPR2022) [paper]
-
A Multi-Head Model for Continual Learning via Out-of-Distribution Replay (CoLLAs2022) [paper] [code]
-
Continual Attentive Fusion for Incremental Learning in Semantic Segmentation (TMM2022) [paper]
-
Self-training for class-incremental semantic segmentation (TNNLS2022) [paper]
-
Effects of Auxiliary Knowledge on Continual Learning (ICPR2022) [paper]
-
Continual Sequence Generation with Adaptive Compositional Modules (ACL2022) [paper]
-
Learngene: From Open-World to Your Learning Task (AAAI2022) [paper] [code]
-
Rethinking the Representational Continuity: Towards Unsupervised Continual Learning (ICLR2022) [paper]
-
Continual Learning with Filter Atom Swapping (ICLR2022) [paper]
-
Continual Learning with Recursive Gradient Optimization (ICLR2022) [paper]
-
TRGP: Trust Region Gradient Projection for Continual Learning (ICLR2022) [paper]
-
Looking Back on Learned Experiences For Class/task Incremental Learning (ICLR2022) [paper]
-
Continual Normalization: Rethinking Batch Normalization for Online Continual Learning (ICLR2022) [paper]
-
Model Zoo: A Growing Brain That Learns Continually (ICLR2022) [paper]
-
Learning curves for continual learning in neural networks: Self-knowledge transfer and forgetting (ICLR2022) [paper]
-
Memory Replay with Data Compression for Continual Learning (ICLR2022) [paper]
-
Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System (ICLR2022) [paper]
-
Online Coreset Selection for Rehearsal-based Continual Learning (ICLR2022) [paper]
-
Pretrained Language Model in Continual Learning: A Comparative Study (ICLR2022) [paper]
-
Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference (ICLR2022) [paper]
-
New Insights on Reducing Abrupt Representation Change in Online Continual Learning (ICLR2022) [paper]
-
Towards Continual Knowledge Learning of Language Models (ICLR2022) [paper]
-
CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability (ICLR2022) [paper]
-
CoMPS: Continual Meta Policy Search (ICLR2022) [paper]
-
Information-theoretic Online Memory Selection for Continual Learning (ICLR2022) [paper]
-
Subspace Regularizers for Few-Shot Class Incremental Learning (ICLR2022) [paper]
-
LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5 (ICLR2022) [paper]
-
Effect of scale on catastrophic forgetting in neural networks (ICLR2022) [paper]
-
Dataset Knowledge Transfer for Class-Incremental Learning without Memory (WACV2022) [paper]
-
Knowledge Capture and Replay for Continual Learning (WACV2022) [paper]
-
Online Continual Learning via Candidates Voting (WACV2022) [paper]
-
lpSpikeCon: Enabling Low-Precision Spiking Neural Network Processing for Efficient Unsupervised Continual Learning on Autonomous Agents (IJCNN2022) [paper]
-
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition (Journal of Imaging 2022) [paper]
2021
- Incremental Object Detection via Meta-Learning (TPAMI 2021) [paper] [code]
- Triple-Memory Networks: A Brain-Inspired Method for Continual Learning (TNNLS 2021) [paper]
- Memory efficient class-incremental learning for image classification (TNNLS 2021) [paper]
- A Procedural World Generation Framework for Systematic Evaluation of Continual Learning (NeurIPS2021) [paper]
- Class-Incremental Learning via Dual Augmentation (NeurIPS2021) [paper]
- SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning (NeurIPS2021) [paper]
- RMM: Reinforced Memory Management for Class-Incremental Learning (NeurIPS2021) [paper]
- Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima (NeurIPS2021) [paper]
- Lifelong Domain Adaptation via Consolidated Internal Distribution (NeurIPS2021) [paper]
- AFEC: Active Forgetting of Negative Transfer in Continual Learning (NeurIPS2021) [paper]
- Natural continual learning: success is a journey, not (just) a destination (NeurIPS2021) [paper]
- Gradient-based Editing of Memory Examples for Online Task-free Continual Learning (NeurIPS2021) [paper]
- Optimizing Reusable Knowledge for Continual Learning via Metalearning (NeurIPS2021) [paper]
- Formalizing the Generalization-Forgetting Trade-off in Continual Learning (NeurIPS2021) [paper]
- Learning where to learn: Gradient sparsity in meta and continual learning (NeurIPS2021) [paper]
- Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning (NeurIPS2021) [paper]
- Posterior Meta-Replay for Continual Learning (NeurIPS2021) [paper]
- Continual Auxiliary Task Learning (NeurIPS2021) [paper]
- Mitigating Forgetting in Online Continual Learning with Neuron Calibration (NeurIPS2021) [paper]
- BNS: Building Network Structures Dynamically for Continual Learning (NeurIPS2021) [paper]
- DualNet: Continual Learning, Fast and Slow (NeurIPS2021) [paper]
- BooVAE: Boosting Approach for Continual Learning of VAE (NeurIPS2021) [paper]
- Generative vs. Discriminative: Rethinking The Meta-Continual Learning (NeurIPS2021) [paper]
- Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning (NeurIPS2021) [paper]
- Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection (NeurIPS, 2021) [paper] [code]
- SS-IL: Separated Softmax for Incremental Learning (ICCV, 2021) [paper]
- Striking a Balance between Stability and Plasticity for Class-Incremental Learning (ICCV, 2021) [paper]
- Synthesized Feature based Few-Shot Class-Incremental Learning on a Mixture of Subspaces (ICCV, 2021) [paper]
- Class-Incremental Learning for Action Recognition in Videos (ICCV, 2021) [paper]
- Continual Prototype Evolution:Learning Online from Non-Stationary Data Streams (ICCV, 2021) [paper]
- Rehearsal Revealed: The Limits and Merits of Revisiting Samples in Continual Learning (ICCV, 2021) [paper]
- Co2L: Contrastive Continual Learning (ICCV, 2021) [paper]
- Wanderlust: Online Continual Object Detection in the Real World (ICCV, 2021) [paper]
- Continual Learning on Noisy Data Streams via Self-Purified Replay (ICCV, 2021) [paper]
- Else-Net: Elastic Semantic Network for Continual Action Recognition from Skeleton Data (ICCV, 2021) [paper]
- Detection and Continual Learning of Novel Face Presentation Attacks (ICCV, 2021) [paper]
- Online Continual Learning with Natural Distribution Shifts: An Empirical Study with Visual Data (ICCV, 2021) [paper]
- Continual Learning for Image-Based Camera Localization (ICCV, 2021) [paper]
- Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting (ICCV, 2021) [paper]
- Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning (ICCV, 2021) [paper]
- RECALL: Replay-based Continual Learning in Semantic Segmentation (ICCV, 2021) [paper]
- Few-Shot and Continual Learning with Attentive Independent Mechanisms (ICCV, 2021) [paper]
- Learning with Selective Forgetting (IJCAI, 2021) [paper]
- Continuous Coordination As a Realistic Scenario for Lifelong Learning (ICML, 2021) [paper]
- Kernel Continual Learning (ICML, 2021) [paper]
- Variational Auto-Regressive Gaussian Processes for Continual Learning (ICML, 2021) [paper]
- Bayesian Structural Adaptation for Continual Learning (ICML, 2021) [paper]
- Continual Learning in the Teacher-Student Setup: Impact of Task Similarity (ICML, 2021) [paper]
- Continuous Coordination As a Realistic Scenario for Lifelong Learning (ICML, 2021) [paper]
- Federated Continual Learning with Weighted Inter-client Transfer (ICML, 2021) [paper]
- Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks (NAACL, 2021) [paper]
- Continual Learning for Text Classification with Information Disentanglement Based Regularization (NAACL, 2021) [paper]
- CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks (EMNLP, 2021) [paper][code]
- Co-Transport for Class-Incremental Learning (ACM MM, 2021) [paper]
- Towards Open World Object Detection (CVPR, 2021) [paper] [code] [video]
- Prototype Augmentation and Self-Supervision for Incremental Learning (CVPR, 2021) [paper] [code]
- ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning (CVPR, 2021) [paper]
- Incremental Learning via Rate Reduction (CVPR, 2021) [paper]
- IIRC: Incremental Implicitly-Refined Classification (CVPR, 2021) [paper]
- Continual Adaptation of Visual Representations via Domain Randomization and Meta-learning (CVPR, 2021) [paper]
- Image De-raining via Continual Learning (CVPR, 2021) [paper]
- Continual Learning via Bit-Level Information Preserving (CVPR, 2021) [paper]
- Hyper-LifelongGAN: Scalable Lifelong Learning for Image Conditioned Generation (CVPR, 2021) [paper]
- Lifelong Person Re-Identification via Adaptive Knowledge Accumulation (CVPR, 2021) [paper]
- Distilling Causal Effect of Data in Class-Incremental Learning (CVPR, 2021) [paper]
- Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning (CVPR, 2021) [paper]
- Layerwise Optimization by Gradient Decomposition for Continual Learning (CVPR, 2021) [paper]
- Adaptive Aggregation Networks for Class-Incremental Learning (CVPR, 2021) [paper]
- Incremental Few-Shot Instance Segmentation (CVPR, 2021) [paper]
- Efficient Feature Transformations for Discriminative and Generative Continual Learning (CVPR, 2021) [paper]
- On Learning the Geodesic Path for Incremental Learning (CVPR, 2021) [paper]
- Few-Shot Incremental Learning with Continually Evolved Classifiers (CVPR, 2021) [paper]
- Rectification-based Knowledge Retention for Continual Learning (CVPR, 2021) [paper]
- DER: Dynamically Expandable Representation for Class Incremental Learning (CVPR, 2021) [paper]
- Rainbow Memory: Continual Learning with a Memory of Diverse Samples (CVPR, 2021) [paper]
- Training Networks in Null Space of Feature Covariance for Continual Learning (CVPR, 2021) [paper]
- Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning (CVPR, 2021) [paper]
- PLOP: Learning without Forgetting for Continual Semantic Segmentation (CVPR, 2021) [paper]
- Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations (CVPR, 2021) [paper]
- Online Class-Incremental Continual Learning with Adversarial Shapley Value(AAAI, 2021) [paper] [code]
- Lifelong and Continual Learning Dialogue Systems: Learning during Conversation(AAAI, 2021) [paper]
- Continual learning for named entity recognition(AAAI, 2021) [paper]
- Using Hindsight to Anchor Past Knowledge in Continual Learning(AAAI, 2021) [paper]
- Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network(AAAI, 2021) [paper] [code]
- Curriculum-Meta Learning for Order-Robust Continual Relation Extraction(AAAI, 2021) [paper]
- Continual Learning by Using Information of Each Class Holistically(AAAI, 2021) [paper]
- Gradient Regularized Contrastive Learning for Continual Domain Adaptation(AAAI, 2021) [paper]
- Unsupervised Model Adaptation for Continual Semantic Segmentation(AAAI, 2021) [paper]
- A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation(AAAI, 2021) [paper]
- Do Not Forget to Attend to Uncertainty While Mitigating Catastrophic Forgetting(WACV, 2021) [paper]
- SpikeDyn: A Framework for Energy-Efficient Spiking Neural Networks with Continual and Unsupervised Learning Capabilities in Dynamic Environments (DAC2021) [paper]
2020
- Rethinking Experience Replay: a Bag of Tricks for Continual Learning(ICPR, 2020) [paper] [code]
- Continual Learning for Natural Language Generation in Task-oriented Dialog Systems(EMNLP, 2020) [paper]
- Distill and Replay for Continual Language Learning(COLING, 2020) [paper]
- Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks (NeurIPS2020) [paper] [code]
- Meta-Consolidation for Continual Learning (NeurIPS2020) [paper]
- Understanding the Role of Training Regimes in Continual Learning (NeurIPS2020) [paper]
- Continual Learning with Node-Importance based Adaptive Group Sparse Regularization (NeurIPS2020) [paper]
- Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning (NeurIPS2020) [paper]
- Coresets via Bilevel Optimization for Continual Learning and Streaming (NeurIPS2020) [paper]
- RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning (NeurIPS2020) [paper]
- Continual Deep Learning by Functional Regularisation of Memorable Past (NeurIPS2020) [paper]
- Dark Experience for General Continual Learning: a Strong, Simple Baseline (NeurIPS2020) [paper] [code]
- GAN Memory with No Forgetting (NeurIPS2020) [paper]
- Calibrating CNNs for Lifelong Learning (NeurIPS2020) [paper]
- Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization (NeurIPS2020) [paper]
- ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation(RecSys, 2020) [paper]
- Initial Classifier Weights Replay for Memoryless Class Incremental Learning (BMVC2020) [paper]
- Adversarial Continual Learning (ECCV2020) [paper] [code]
- REMIND Your Neural Network to Prevent Catastrophic Forgetting (ECCV2020) [paper] [code]
- Incremental Meta-Learning via Indirect Discriminant Alignment (ECCV2020) [paper]
- Memory-Efficient Incremental Learning Through Feature Adaptation (ECCV2020) [paper]
- PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning (ECCV2020) [paper] [code]
- Reparameterizing Convolutions for Incremental Multi-Task Learning Without Task Interference (ECCV2020) [paper]
- Learning latent representions across multiple data domains using Lifelong VAEGAN (ECCV2020) [paper]
- Online Continual Learning under Extreme Memory Constraints (ECCV2020) [paper]
- Class-Incremental Domain Adaptation (ECCV2020) [paper]
- More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning (ECCV2020) [paper]
- Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation (ECCV2020) [paper]
- GDumb: A Simple Approach that Questions Our Progress in Continual Learning (ECCV2020) [paper]
- Imbalanced Continual Learning with Partitioning Reservoir Sampling (ECCV2020) [paper]
- Topology-Preserving Class-Incremental Learning (ECCV2020) [paper]
- GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems (CIKM2020) [paper]
- OvA-INN: Continual Learning with Invertible Neural Networks (IJCNN2020) [paper]
- XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning (ICLM2020) [paper]
- Optimal Continual Learning has Perfect Memory and is NP-HARD (ICML2020) [paper]
- Neural Topic Modeling with Continual Lifelong Learning (ICML2020) [paper]
- Continual Learning with Knowledge Transfer for Sentiment Classification (ECML-PKDD2020) [paper] [code]
- Semantic Drift Compensation for Class-Incremental Learning (CVPR2020) [paper] [code]
- Few-Shot Class-Incremental Learning (CVPR2020) [paper]
- Modeling the Background for Incremental Learning in Semantic Segmentation (CVPR2020) [paper]
- Incremental Few-Shot Object Detection (CVPR2020) [paper]
- Incremental Learning In Online Scenario (CVPR2020) [paper]
- Maintaining Discrimination and Fairness in Class Incremental Learning (CVPR2020) [paper]
- Conditional Channel Gated Networks for Task-Aware Continual Learning (CVPR2020) [paper]
- Continual Learning with Extended Kronecker-factored Approximate Curvature (CVPR2020) [paper]
- iTAML : An Incremental Task-Agnostic Meta-learning Approach (CVPR2020) [paper] [code]
- Mnemonics Training: Multi-Class Incremental Learning without Forgetting (CVPR2020) [paper] [code]
- ScaIL: Classifier Weights Scaling for Class Incremental Learning (WACV2020) [paper]
- Accepted papers(ICLR2020) [paper]
- Brain-inspired replay for continual learning with artificial neural networks (Natrue Communications 2020) [paper] [code]
- Learning to Continually Learn (ECAI 2020) [paper] [code]
2019
- Compacting, Picking and Growing for Unforgetting Continual Learning (NeurIPS2019)[paper][code]
- Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning (ICMR2019) [paper][code]
- Towards Training Recurrent Neural Networks for Lifelong Learning (Neural Computation 2019) [paper]
- Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay (IJCAI2019) [paper]
- IL2M: Class Incremental Learning With Dual Memory (ICCV2019) [paper]
- Incremental Learning Using Conditional Adversarial Networks (ICCV2019) [paper]
- Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability (KDD2019) [paper]
- Random Path Selection for Incremental Learning (NeurIPS2019) [paper]
- Online Continual Learning with Maximal Interfered Retrieval (NeurIPS2019) [paper]
- Meta-Learning Representations for Continual Learning (NeurIPS2019) [paper] [code]
- Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild (ICCV2019) [paper]
- Continual Learning by Asymmetric Loss Approximation with Single-Side Overestimation (ICCV2019) [paper]
- Lifelong GAN: Continual Learning for Conditional Image Generation (ICCV2019) [paper]
- Continual learning of context-dependent processing in neural networks (Nature Machine Intelligence 2019) [paper] [code]
- Large Scale Incremental Learning (CVPR2019) [paper] [code]
- Learning a Unified Classifier Incrementally via Rebalancing (CVPR2019) [paper] [code]
- Learning Without Memorizing (CVPR2019) [paper]
- Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning (CVPR2019) [paper]
- Task-Free Continual Learning (CVPR2019) [paper]
- Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting (ICML2019) [paper]
- Efficient Lifelong Learning with A-GEM (ICLR2019) [paper] [code]
- Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference (ICLR2019) [paper] [code]
- Overcoming Catastrophic Forgetting via Model Adaptation (ICLR2019) [paper]
- A comprehensive, application-oriented study of catastrophic forgetting in DNNs (ICLR2019) [paper]
2018
- Memory Replay GANs: learning to generate images from new categories without forgetting (NIPS2018) [paper] [code]
- Reinforced Continual Learning (NIPS2018) [paper] [code]
- Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting (NIPS2018) [paper]
- Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting (R-EWC) (ICPR2018) [paper] [code]
- Exemplar-Supported Generative Reproduction for Class Incremental Learning (BMVC2018) [paper] [code]
- End-to-End Incremental Learning (ECCV2018) [paper][code]
- Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence (ECCV2018)[paper]
- Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights (ECCV2018) [paper] [code]
- Memory Aware Synapses: Learning what (not) to forget (ECCV2018) [paper] [code]
- Lifelong Learning via Progressive Distillation and Retrospection (ECCV2018) [paper]
- PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning (CVPR2018) [paper] [code]
- Overcoming Catastrophic Forgetting with Hard Attention to the Task (ICML2018) [paper] [code]
- Lifelong Learning with Dynamically Expandable Networks (ICLR2018) [paper]
- FearNet: Brain-Inspired Model for Incremental Learning (ICLR2018) [paper]
2017
- Incremental Learning of Object Detectors Without Catastrophic Forgetting (ICCV2017) [paper]
- Overcoming catastrophic forgetting in neural networks (EWC) (PNAS2017) [paper] [code] [code]
- Continual Learning Through Synaptic Intelligence (ICML2017) [paper] [code]
- Gradient Episodic Memory for Continual Learning (NIPS2017) [paper] [code]
- iCaRL: Incremental Classifier and Representation Learning (CVPR2017) [paper] [code]
- Continual Learning with Deep Generative Replay (NIPS2017) [paper] [code]
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (NIPS2017) [paper] [code]
- Expert Gate: Lifelong Learning with a Network of Experts (CVPR2017) [paper]
- Encoder Based Lifelong Learning (ICCV2017) [paper]
2016
- Learning without forgetting (ECCV2016) [paper] [code]
Awesome Long-Tailed Recognition / Imbalanced Learning
Find it interesting that there are more shared techniques than I thought for incremental learning (exemplars-based).
ContinualAI wiki
An Open Community of Researchers and Enthusiasts on Continual/Lifelong Learning for AI
Workshops
4th Lifelong Learning Workshop at ICML 2020
Workshop on Continual Learning at ICML 2020
Continual Learning in Computer Vision Workshop CVPR 2020
Continual learning workshop NeurIPS 2018
Challenges or Competitions
1st Lifelong Learning for Machine Translation Shared Task at WMT20 (EMNLP 2020)
Continual Learning in Computer Vision Challenge CVPR 2020
Lifelong Robotic Vision Challenge IROS 2019
Feel free to contact me if you find any interesting paper is missing.
Workshop papers are currently out due to space.
Related repositories
Master programming by recreating your favorite technologies from scratch.
A curated meta-list of curated lists organized by technology domain. The repository acts as a directory pointing to hundreds of specialized awesome lists covering programming languages, platforms, frameworks, and tooling. All content is community-contributed under the CC0 public domain dedication.
Public APIs is a community-curated GitHub repository listing free, publicly accessible APIs across a wide range of categories, with auth type, HTTPS, and CORS noted for each entry. It's a browsable reference, not a library to install.
freeCodeCamp is a free, self-paced curriculum for learning to code, published as open source at freeCodeCamp/freeCodeCamp. It's a 501(c)(3) nonprofit funded by donor support, structured around six certifications in its Full-Stack Developer Curriculum, each gated by required projects instead of open-book quizzes. The repository also carries beta language certifications for developers, interview-prep resources, and the code that runs the live freecodecamp.org platform.
Quick answers
How active is development on xialeiliu/Awesome-Incremental-Learning?
The most recent commit recorded on xialeiliu/Awesome-Incremental-Learning was 17 days ago, based on the GitHub push timestamp. The repository has 628 forks — one of the better signals of community interest.
How many stars does xialeiliu/Awesome-Incremental-Learning have?
xialeiliu/Awesome-Incremental-Learning has 4.5k GitHub stars — refresh the page for the live number, or check github.com/xialeiliu/Awesome-Incremental-Learning. TopGit mirrors GitHub's count but does not claim minute-by-minute accuracy.
Is xialeiliu/Awesome-Incremental-Learning open source?
TopGit's metadata for xialeiliu/Awesome-Incremental-Learning does not record a license. Most public repositories on GitHub ARE open source, but the exact terms vary — verify by opening the LICENSE file directly.
What is xialeiliu/Awesome-Incremental-Learning?
xialeiliu/Awesome-Incremental-Learning (xialeiliu/Awesome-Incremental-Learning) is a multi-language project on GitHub. From the project's own README: Awesome Incremental Learning
Where do I read more about xialeiliu/Awesome-Incremental-Learning?
This TopGit page is a snapshot — the READ ME tab shows the project's own README content (links stripped, images preserved). The GitHub repository at github.com/xialeiliu/Awesome-Incremental-Learning is the definitive source.
Read full README in the tab above.
Is Awesome-Incremental-Learning worth your time?
ChatGPT, Claude and Perplexity can all read this page. Ask one of them what it makes of Awesome-Incremental-Learning.