This repository contains a curated list of continual learning papers and BibTeX entries (mostly until 2022).
- (Book 18) Lifelong Machine Learning
- (PhD dissertation 19) Continual Learning with Deep Architectures
- (PhD dissertation 19) Continual Learning in Neural Networks
- (Trends in Cognitive Science 20) Embracing Change: Continual Learning in Deep Neural Networks
- (TPAMI 21) A Continual Learning Survey: Defying Forgetting in Classification Tasks
- (JAIR 22) Towards Continual Reinforcement Learning: A Review and Perspectives
- (Neurocomputing 22) Online Continual Learning in Image Classification: An Empirical Survey
- (arXiv 22) An Introduction to Lifelong Supervised Learning
- (Trends in Neurosciences 23) Continual Task Learning in Natural and Artificial Agents
- (Neural Networks 23) A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
- (arXiv 23) A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
- (TPAMI 24) A Comprehensive Survey of Continual Learning: Theory, Method and Application
- (TPAMI 24) Class-Incremental Learning: A Survey
- (IJCAI 24) Continual Learning with Pre-Trained Models: A Survey
- (arXiv 24) Continual Learning of Large Language Models: A Comprehensive Survey
- (arXiv 24) Recent Advances of Multimodal Continual Learning: A Comprehensive Survey
- (CVPR 17) iCaRL: Incremental Classifier and Representation Learning
- (NeurIPS 17) Gradient Episodic Memory for Continual Learning
- (ECCV 18) End-to-End Incremental Learning
- (ICLR 19) Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference
- (ICLR 19) Efficient Lifelong Learning with A-GEM
- (CVPR 19) Large Scale Incremental Learning
- (CVPR 19) Learning a Unified Classifier Incrementally via Rebalancing
- (NeurIPS 19) Experience Replay for Continual Learning
- (NeurIPS 19) Gradient based Sample Selection for Online Continual Learning
- (NeurIPS 19) Online Continual Learning with Maximal Interfered Retrieval
- (ICMLW 19) On Tiny Episodic Memories in Continual Learning
- (ECCV 20) GDumb: A Simple Approach that Questions Our Progress in Continual Learning
- (NeurIPS 20) Coresets via Bilevel Optimization for Continual Learning and Streaming
- (NeurIPS 20) Dark Experience for General Continual Learning: A Strong, Simple Baseline
- (ICPR 20) Rethinking Experience Replay: A Bag of Tricks for Continual Learning
- (AAAI 21) Using Hindsight to Anchor Past Knowledge in Continual Learning
- (ICLR 21) Dataset Condensation with Gradient Matching
- (CVPR 21) Rainbow Memory: Continual Learning with a Memory of Diverse Samples
- (ICML 21) Grad-Match: Gradient Matching Based Data Subset Selection for Efficient Deep Model Training
- (ICCV 21) Rehearsal Revealed: The Limits and Merits of Revisiting Samples in Continual Learning
- (NeurIPS 21) Gradient-based Editing of Memory Examples for Online Task-free Continual Learning
- (NeurIPS 21) RMM: Reinforced Memory Management for Class-Incremental Learning
- (NeurIPSW 21) Gradient-Matching Coresets for Continual Learning
- (ICLR 22) Online Coreset Selection for Rehearsal-based Continual Learning
- (ICLR 22) New Insights on Reducing Abrupt Representation Change in Online Continual Learning
- (ICLR 22) Memory Replay with Data Compression for Continual Learning
- (CVPR 22) GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning
- (ICML 22) Improving Task-free Continual Learning by Distributionally Robust Memory Evolution
- (ICML 22) Online Continual Learning through Mutual Information Maximization
- (NeurIPS 22) Exploring Example Influence in Continual Learning
- (NeurIPS 22) Retrospective Adversarial Replay for Continual Learning
- (NeurIPS 22) Repeated Augmented Rehearsal: A Simple but Strong Baseline for Online Continual Learning
- (TPAMI 22) Class-Incremental Continual Learning into the eXtended DER-verse
- (ICLR 23) Error Sensitivity Modulation based Experience Replay: Mitigating Abrupt Representation Drift in Continual Learning
- (CVPR 23) Computationally Budgeted Continual Learning: What Does Matter?
- (CVPR 23) Class-Incremental Exemplar Compression for Class-Incremental Learning
- (CVPR 23) PCR: Proxy-based Contrastive Replay for Online Class-Incremental Continual Learning
- (CVPR 23) Rebalancing Batch Normalization for Exemplar-based Class-Incremental Learning
- (CVPR 23) Regularizing Second-Order Influences for Continual Learning
- (ICML 23) BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning
- (ICML 23) DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning
- (IJCV 23) Trust-Region Adaptive Frequency for Online Continual Learning
- (NeurIPS 17) Continual Learning with Deep Generative Replay
- (NeurIPS 18) Memory Replay GANs: Learning to Generate New Categories without Forgetting
- (NeurIPS 20) GAN Memory with No Forgetting
- (Nature Communications 20) Brain-Inspired Replay for Continual Learning with Artificial Neural Networks
- (Neurocomputing 20) Lifelong Generative Modeling
- (ICCV 21) Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning
- (CVPR 22) Learning to Imagine: Diversify Memory for Incremental Learning using Unlabeled Data
- (ICLR 23) Incremental Learning of Structured Memory via Closed-Loop Transcription
- (ICML 23) DDGR: Continual Learning with Deep Diffusion-based Generative Replay
- (BMVC 24) CLIP with Generative Latent Replay: a Strong Baseline for Incremental Learning
- (ICML 17) Continual Learning through Synaptic Intelligence
- (ECCV 18) Memory Aware Synapses: Learning What (Not) to Forget
- (ECCV 18) Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
- (NeurIPS 20) Understanding the Role of Training Regimes in Continual Learning
- (CVPR 23) Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning
- (ICLR 24) A Unified and General Framework for Continual Learning
- (PNAS 17) Overcoming Catastrophic Forgetting in Neural Networks
- (NeurIPS 17) Overcoming Catastrophic Forgetting by Incremental Moment Matching
- (NeurIPS 18) Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting
- (ICLR 18) Variational Continual Learning
- (NeurIPS 19) Uncertainty-based Continual Learning with Adaptive Regularization
- (ICLR 20) Uncertainty-guided Continual Learning with Bayesian Neural Networks
- (ICLR 20) Continual Learning with Adaptive Weights (CLAW)
- (NeurIPS 21) Natural Continual Learning: Success Is a Journey, Not (Just) A Destination
- (NeurIPS 21) AFEC: Active Forgetting of Negative Transfer in Continual Learning
- (AISTATS 22) Provable Continual Learning via Sketched Jacobian Approximations
- (ICIF 2024) Adaptive Robust Continual Learning based on Bayesian Uncertainty Propagation
- (Nature Machine Intelligence 19) Continual Learning of Context-Dependent Processing in Neural Networks
- (AISTATS 20) Orthogonal Gradient Descent for Continual Learning
- (NeurIPS 20) Continual Learning in Low-rank Orthogonal Subspaces
- (ICLR 21) Gradient Projection Memory for Continual Learning
- (ICLR 21) Linear Mode Connectivity in Multitask and Continual Learning
- (CVPR 21) Training Networks in Null Space of Feature Covariance for Continual Learning
- (CVPR 21) Layerwise Optimization by Gradient Decomposition for Continual Learning
- (NeurIPS 21) Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning
- (ICLR 22) TRGP: Trust Region Gradient Projection for Continual Learning
- (ICLR 22) Continual Learning with Recursive Gradient Optimization
- (ICML 22) Continual Learning with Guarantees via Weight Interval Constraints
- (CVPR 22) Towards Better Plasticity-Stability Trade-off in Incremental Learning: A Simple Linear Connector
- (AAAI 23) Continual Learning with Scaled Gradient Projection
- (ICLR 23) Building a Subspace of Policies for Scalable Continual Learning
- (CVPR 23) Adaptive Plasticity Improvement for Continual Learning
- (CVPR 23) Decoupling Learning and Remembering: a Bilevel Memory Framework with Knowledge Projection for Task-Incremental Learning
- (ICML 23) Optimizing Mode Connectivity for Class Incremental Learning
- (ICCV 23) Data Augmented Flatness-aware Gradient Projection for Continual Learning
- (ICLR 24) Prompt Gradient Projection for Continual Learning
- (TPAMI 17) Learning without Forgetting
- (CVPR 19) Learning without Memorizing
- (CVPR 20) Few-Shot Class-Incremental Learning
- (ECCV 20) Topology-Preserving Class-Incremental Learning
- (ICCV 21) Co^2^L: Contrastive Continual Learning
- (TIP 22) CKDF: Cascaded Knowledge Distillation Framework for Robust Incremental Learning
- (TPAMI 23) Variational Data-Free Knowledge Distillation for Continual Learning
- (ICML 23) Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning
- (ICCV 23) Dynamic Residual Classifier for Class Incremental Learning
- (ICCV 23) Prototype Reminiscence and Augmented Asymmetric Knowledge Aggregation for Non-Exemplar Class-Incremental Learning
- (ICLR 20) Continual Learning with Hypernetworks
- (NeurIPS 21) DualNet: Continual Learning, Fast and Slow
- (ICLR 22) Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System
- (ICLR 22) Model Zoo: A Growing Brain That Learns Continually
- (ECCV 22) CoSCL: Cooperation of Small Continual Learners is Stronger Than a Big One
- (CVPR 23) Bilateral Memory Consolidation for Continual Learning
- (ICCV 23) Growing a Brain with Sparsity-Inducing Generation for Continual Learning
- (ICLR 24) Divide and Not Forget: Ensemble of Selectively Trained Experts in Continual Learning
- (AAAI 24) Evolving Parameterized Prompt Memory for Continual Learning
- (ICLR 16) Net2Net: Accelerating Learning via Knowledge Transfer
- (arXiv 16) Progressive Neural Networks
- (CVPR 17) Expert Gate: Lifelong Learning with a Network of Experts
- (ICML 17) AdaNet: Adaptive Structural Learning of Artificial Neural Networks
- (ICLR 18) Lifelong Learning with Dynamically Expandable Networks
- (ICML 19) Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting
- (ICLR 20) A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning
- (ECCV 20) Side-Tuning: A Baseline for Network Adaptation via Additive Side Networks
- (NeurIPS 20) Calibrating CNNs for Lifelong Learning
- (CVPR 21) DER: Dynamically Expandable Representation for Class Incremental Learning
- (CVPR 21) Adaptive Aggregation Networks for Class-Incremental Learning
- (NeurIPS 21) BNS: Building Network Structures Dynamically for Continual Learning
- (CVPR 22) DyTox: Transformers for Continual Learning with Dynamic Token Expansion
- (CVPR 22) Learning to Prompt for Continual Learning
- (ECCV 22) DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning
- (ECCV 22) FOSTER: Feature Boosting and Compression for Class-Incremental Learning
- (NeurIPS 22) S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning
- (TPAMI 22) Adaptive Progressive Continual Learning
- (ICLR 23) Progressive Prompts: Continual Learning for Language Models
- (ICLR 23) A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning
- (CVPR 23) Task Difficulty Aware Parameter Allocation & Regularization for Lifelong Learning
- (CVPR 23) Dense Network Expansion for Class Incremental Learning
- (CVPR 23) DKT: Diverse Knowledge Transfer Transformer for Class Incremental Learning
- (CVPR 23) CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning
- (ICML 23) Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks
- (ICML 23) Lifelong Language Pretraining with Distribution-Specialized Experts
- (ICCV 23) A Unified Continual Learning Framework with General Parameter-Efficient Tuning
- (ICCV 23) CLR: Channel-wise Lightweight Reprogramming for Continual Learning
- (ICCV 23) Exemplar-Free Continual Transformer with Convolutions
- (ICCV 23) Self-Evolved Dynamic Expansion Model for Task-Free Continual Learning
- (ICCV 23) Tangent Model Composition for Ensembling and Continual Fine-tuning
- (ICCV 23) Generating Instance-level Prompts for Rehearsal-free Continual Learning
- (ICCV 23) Self-Organizing Pathway Expansion for Non-Exemplar Class-Incremental Learning
- (NeurIPS 23) Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality
- (CVPR 24) Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning
- (CVPR 24) InfLoRA: Interference-Free Low-Rank Adaptation for Continual Learning
- (CVPR 18) PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning
- (ICML 18) Overcoming Catastrophic Forgetting with Hard Attention to the Task
- (NeurIPS 19) Random Path Selection for Incremental Learning
- (NeurIPSW 19) Continual Learning via Neural Pruning
- (NeurIPS 20) Supermasks in Superposition
- (ICLR 21) Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning
- (CVPR 21) Continual Learning via Bit-Level Information Preserving
- (CVPR 22) Meta-Attention for ViT-backed Continual Learning
- (ICML 22) Forget-free Continual Learning with Winning Subnetworks
- (ICML 22) NISPA: Neuro-Inspired Stability-Plasticity Adaptation for Continual Learning in Sparse Networks
- (ICML 23) Discrete Key-Value Bottleneck
- (ICML 23) Parameter-Level Soft-Masking for Continual Learning
- (ICLR 24) Scalable Language Model With Generalized Continual Learning
- (AAAI 24) MIND: Multi-Task Incremental Network Distillation
- (ICLR 20) Scalable and Order-robust Continual Learning with Additive Parameter Decomposition
- (ICLR 20) BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning
- (CVPR 21) Efficient Feature Transformations for Discriminative and Generative Continual Learning
- (NeurIPS 21) Mitigating Forgetting in Online Continual Learning with Neuron Calibration
- (NeurIPS 21) Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning
- (ICLR 22) TRGP: Trust Region Gradient Projection for Continual Learning
- (TKDE 24) Hessian Aware Low-Rank Perturbation for Order-Robust Continual Learning
This is a collection for more theoretical continual learning papers. Feel free to commit!
- (NeurIPS 22) A Theoretical Study on Solving Continual Learning
- (NeurIPS 22) ACIL: Analytic class-incremental learning with absolute memorization and privacy protection
- (CVPR 23) GKEAL: Gaussian kernel embedded analytic learning for few-shot class incremental task
- (NeurIPS 23) A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm
- (AAAI 24) DS-AL: A Dual-Stream Analytic Learning for Exemplar-Free Class-Incremental Learning
- (ICCV 17) Incremental Learning of Object Detectors without Catastrophic Forgetting
- (WACV 20) Class-incremental Learning via Deep Model Consolidation
- (CVPR 20) Incremental Few-Shot Object Detection
- (CVPR 21) Towards Open World Object Detection
- (ICCV 21) Wanderlust: Online Continual Object Detection in the Real World
- (NeurIPS 21) Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection
- (TPAMI 21) Incremental Object Detection via Meta-Learning
- (CVPR 22) Overcoming Catastrophic Forgetting in Incremental Object Detection via Elastic Response Distillation
- (CVPR 22) Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism
- (CVPR 22) OW-DETR: Open-world Detection Transformer
- (ECCV 22) UC-OWOD: Unknown-Classified Open World Object Detection
- (CVPR 23) Continual Detection Transformer for Incremental Object Detection
- (CVPR 23) CAT: LoCalization and IdentificAtion Cascade Detection Transformer for Open-World Object Detection
- (CVPR 23) PROB: Probabilistic Objectness for Open World Object Detection
- (CVPR 23) Annealing-based Label-Transfer Learning for Open World Object Detection
- (ICCV 23) Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection
- (ICCV 23) Label-Efficient Online Continual Object Detection in Streaming Video
- (ICCV 23) Random Boxes Are Open-world Object Detectors
- (CVPR 24) SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection
- (CVPR 24) Exploring Orthogonality in Open World Object Detection
- (ICCVW 19) Incremental Learning Techniques for Semantic Segmentation
- (CVPR 20) Modeling the Background for Incremental Learning in Semantic Segmentation
- (AAAI 21) A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation
- (AAAI 21) Unsupervised Model Adaptation for Continual Semantic Segmentation
- (CVPR 21) Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations
- (CVPR 21) PLOP: Learning without Forgetting for Continual Semantic Segmentation
- (CVPR 21) Incremental Few-Shot Instance Segmentation
- (ICCV 21) RECALL: Replay-based Continual Learning in Semantic Segmentation
- (NeurIPS 21) SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning
- (WACV 22) Multi-Domain Incremental Learning for Semantic Segmentation
- (CVPR 22) Representation Compensation Networks for Continual Semantic Segmentation
- (CVPR 22) Class Similarity Weighted Knowledge Distillation for Continual Semantic Segmentation
- (CVPR 22) Incremental Learning in Semantic Segmentation from Image Labels
- (CVPR 22) Learning Multiple Dense Prediction Tasks from Partially Annotated Data
- (ECCV 22) RBC: Rectifying the Biased Context in Continual Semantic Segmentation
- (ECCV 22) Continual Semantic Segmentation via Structure Preserving and Projected Feature Alignment
- (NeurIPS 22) Decomposed Knowledge Distillation for Class-Incremental Semantic Segmentation
- (NeurIPS 22) ALIFE: Adaptive Logit Regularizer and Feature Replay for Incremental Semantic Segmentation
- (NeurIPS 22) Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation
- (TPAMI 22) Modeling the Background for Incremental and Weakly-Supervised Semantic Segmentation
- (TPAMI 22) Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
- (TNNLS 22) Self-Training for Class-Incremental Semantic Segmentation
- (CVPR 23) Foundation Model Drives Weakly Incremental Learning for Semantic Segmentation
- (CVPR 23) CoMFormer: Continual Learning in Semantic and Panoptic Segmentation
- (CVPR 23) Continual Semantic Segmentation with Automatic Memory Sample Selection
- (CVPR 23) Principles of Forgetting in Domain-Incremental Semantic Segmentation in Adverse Weather Conditions
- (CVPR 23) Unsupervised Continual Semantic Adaptation through Neural Rendering
- (CVPR 23) Federated Incremental Semantic Segmentation
- (CVPR 23) Incrementer: Transformer for Class-Incremental Semantic Segmentation with Knowledge Distillation Focusing on Old Class
- (CVPR 23) Endpoints Weight Fusion for Class Incremental Semantic Segmentation
- (ICCV 23) Label-Guided Knowledge Distillation for Continual Semantic Segmentation on 2D Images and 3D Point Clouds
- (ICCV 23) Preparing the Future for Continual Semantic Segmentation
- (ICCV 23) Class-incremental Continual Learning for Instance Segmentation with Image-level Weak Supervision
- (NeurIPS 23) Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments
- (CVPR 24) Continual Segmentation with Disentangled Objectness Learning and Class Recognition
- (NeurIPS 18) Memory Replay GANs: Learning to Generate New Categories without Forgetting
- (ICCV 19) Lifelong GAN: Continual Learning for Conditional Image Generation
- (ECCV 20) Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation
- (CVPR 21) Hyper-LifelongGAN: Scalable Lifelong Learning for Image Conditioned Generation
- (CVPR 21) Efficient Feature Transformations for Discriminative and Generative Continual Learning
- (ICCV 23) LFS-GAN: Lifelong Few-Shot Image Generation
- (NeurIPS 23) Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models
- (AVSS 19) Continuous Learning without Forgetting for Person Re-Identification
- (AAAI 21) Generalising without Forgetting for Lifelong Person Re-Identification
- (WACV 21) Continual Representation Learning for Biometric Identification
- (CVPR 21) Lifelong Person Re-Identification via Adaptive Knowledge Accumulation
- (AAAI 22) Lifelong Person Re-identification by Pseudo Task Knowledge Preservation
- (CVPR 22) Lifelong Unsupervised Domain Adaptive Person Re-Identification with Coordinated Anti-forgetting and Adaptation
- (ACM MM 22) Meta Reconciliation Normalization for Lifelong Person Re-Identification
- (ACM MM 22) Patch-based Knowledge Distillation for Lifelong Person Re-Identification
- (BMVC 22) Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification
- (ACM MM 23) Handling Label Uncertainty for Camera Incremental Person Re-Identification
- (CVPR 24) Distribution-aware Knowledge Prototyping for Non-exemplar Lifelong Person Re-identification
- (CVPR 24) Learning Continual Compatible Representation for Re-indexing Free Lifelong Person Re-identification
- (ACL 19) Psycholinguistics Meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question Answering
- (EMNLP 20) Visually Grounded Continual Learning of Compositional Phrases
- (NeurIPS 20) RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning
- (ECCV 22) Generative Negative Text Replay for Continual Vision-Language Pretraining
- (NeurIPS 22) BMU-MoCo: Bidirectional Momentum Update for Continual Video-Language Modeling
- (AAAI 23) Symbolic Replay: Scene Graph as Prompt for Continual Learning on VQA Task
- (CVPR 23) ConStruct-VL: Data-Free Continual Structured VL Concepts Learning
- (CVPR 23) VQACL: A Novel Visual Question Answering Continual Learning Setting
- (ICML 23) Open-VCLIP: Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization
- (ICML 23) Continual Vision-Language Representation Learning with Off-Diagonal Information
- (ICCV 23) Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models
- (ICCV 23) CTP: Towards Vision-Language Continual Pretraining via Compatible Momentum Contrast and Topology Preservation
- (ICCV 23) Decouple Before Interact: Multi-Modal Prompt Learning for Continual Visual Question Answering
- (AAAI 24) Continual Vision-Language Retrieval via Dynamic Knowledge Rectification
- (ICLR 24) TiC-CLIP: Continual Training of CLIP Models
- (CVPR 24) Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters
- (ECCV 24) Mind the Interference: Retaining Pre-trained Knowledge in Parameter Efficient Continual Learning of Vision-Language Models
- (AAAI 18) Selective Experience Replay for Lifelong Learning
- (ICLR 18) Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
- (ICLR 18) Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control
- (ICML 18) State Abstractions for Lifelong Reinforcement Learning
- (ICML 18) Policy and Value Transfer in Lifelong Reinforcement Learning
- (ICML 18) Continual Reinforcement Learning with Complex Synapses
- (NeurIPS 18) Lifelong Inverse Reinforcement Learning
- (ICLR 19) Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL
- (ICLR 19) Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference
- (ICML 19) Policy Consolidation for Continual Reinforcement Learning
- (NeurIPS 19) Experience Replay for Continual Learning
- (NeurIPS 20) Deep Reinforcement and InfoMax Learning
- (NeurIPS 20) Continual Learning of Control Primitives: Skill Discovery via Reset-Games
- (NeurIPS 20) Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes
- (NeurIPS 20) Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting
- (ICLR 21) CoMPS: Continual Meta Policy Search
- (ICLR 21) Reset-Free Lifelong Learning with Skill-Space Planning
- (Neurocomputing 21) Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting
- (AAAI 22) Same State, Different Task: Continual Reinforcement Learning without Interference
- (ICLR 22) Modular Lifelong Reinforcement Learning via Neural Composition
- (ICLR 22) Generalisation in Lifelong Reinforcement Learning through Logical Composition
- (NeurIPS 22) Model-based Lifelong Reinforcement Learning with Bayesian Exploration
- (NeurIPS 22) Continual Learning In Environments With Polynomial Mixing Times
- (NeurIPS 22) Disentangling Transfer in Continual Reinforcement Learning
- (ICLR 23) Building a Subspace of Policies for Scalable Continual Learning
- (ICML 23) Continual Task Allocation in Meta-Policy Network via Sparse Prompting
- (NeurIPS 23) A Definition of Continual Reinforcement Learning
- (NeurIPS 23) Rewiring Neurons in Non-Stationary Environments
- (NeurIPS 19) A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning
- (NeurIPS 19) Non-Stationary Markov Decision Processes a Worst-Case Approach using Model-Based Reinforcement Learning
- (AAAI 20) Lifelong Learning with a Changing Action Set
- (ICML 20) Optimizing for the Future in Non-Stationary MDPs
- (NeurIPS 20) Dynamic Regret of Policy Optimization in Non-stationary Environments
- (NeurIPS 20) Towards Safe Policy Improvement for Non-Stationary MDPs
- (AAAI 21) Lipschitz Lifelong Reinforcement Learning
- (ICML 21) Deep Reinforcement Learning amidst Continual Structured Non-Stationarity
- (ICLR 22) Reinforcement Learning in Presence of Discrete Markovian Context Evolution
- (NeurIPS 22) Off-Policy Evaluation for Action-Dependent Non-stationary Environments
- (NeurIPS 22) Factored Adaptation for Non-Stationary Reinforcement Learning
- (SIGGRAPH 19) Unsupervised Incremental Learning for Hand Shape and Pose Estimation
- (AAAI 20) Generative Continual Concept Learning
- (CVPR 20) Online Depth Learning against Forgetting in Monocular Videos
- (ECCV 20) SPARK: Spatial-aware Online Incremental Attack Against Visual Tracking
- (IROS 20) Latent Replay for Real-Time Continual Learning
- (CVPRW 20) Continual Learning for Anomaly Detection in Surveillance Videos
- (CVPRW 20) Continual Learning of Object Instances
- (ICMLW 20) Continual Learning in Human Activity Recognition: an Empirical Analysis of Regularization
- (arXiv 20) Learning Causal Models Online
- (AAAI 21) Continual Learning for Named Entity Recognition
- (CVPR 21) Image De-raining via Continual Learning
- (CVPRW 21) Selective Replay Enhances Learning in Online Continual Analogical Reasoning
- (ICCV 21) Class-Incremental Learning for Action Recognition in Videos
- (ICCV 21) Else-Net: Elastic Semantic Network for Continual Action Recognition from Skeleton Data
- (ICCV 21) Detection and Continual Learning of Novel Face Presentation Attacks
- (ICCV 21) Continual Learning for Image-Based Camera Localization
- (ICCV 21) Continual Neural Mapping: Learning An Implicit Scene Representation from Sequential Observations
- (BMVC 21) Incremental Learning for Animal Pose Estimation using RBF k-DPP
- (WWW 22) Multimodal Continual Graph Learning with Neural Architecture Search
- (CVPR 22) Lifelong Graph Learning
- (CVPR 22) Continual Test-Time Domain Adaptation
- (ICML 22) Efficient Test-Time Model Adaptation without Forgetting
- (ECCV 22) Novel Class Discovery without Forgetting
- (ECCV 22) incDFM: Incremental Deep Feature Modeling for Continual Novelty Detection
- (AISTATS 22) Online Continual Adaptation with Active Self-Training
- (ACL 22) Continual Prompt Tuning for Dialog State Tracking
- (Findings of ACL 22) Consistent Representation Learning for Continual Relation Extraction
- (COLING 22) Continuous Detection, Rapidly React: Unseen Rumors Detection based on Continual Prompt-Tuning
- (RA-L 22) Improving Pedestrian Prediction Models with Self-Supervised Continual Learning
- (ICLR 23) Towards Open Temporal Graph Neural Networks
- (WWW 23) Dynamically Expandable Graph Convolution for Streaming Recommendation
- (CVPR 23) Cloud-Device Collaborative Adaptation to Continual Changing Environments in the Real-world
- (CVPR 23) PIVOT: Prompting for Video Continual Learning
- (CVPR 23) Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic Segmentation
- (ICCV 23) CLNeRF: Continual Learning Meets NeRF
- (ICCV 23) Active Neural Mapping
- (ICCV 23) GFM: Building Geospatial Foundation Models via Continual Pretraining
- (ICCV 23) Rehearsal-Free Domain Continual Face Anti-Spoofing: Generalize More and Forget Less
- (ICCV 23) Towards Realistic Evaluation of Industrial Continual Learning Scenarios with an Emphasis on Energy Consumption and Computational Footprint
- (NeurIPS 23) Temporal Continual Learning with Prior Compensation for Human Motion Prediction
- (NeurIPS 23) CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation
- (ICLR 24) Online Continual Learning for Interactive Instruction Following Agents
- (ICLR 24) Two-stage LLM Fine-tuning with Less Specialization and More Generalization
- (ICLR 24) CPPO: Continual Learning for Reinforcement Learning With Human Feedback
- (ICLR 24) Scalable Language Model with Generalized Continual Learning
- (CVPR 24) GOAT-Bench: A Benchmark for Multi-modal Lifelong Navigation
- (CVPR 24) ICON: Incremental CONfidence for Joint Pose and Radiance Field Optimization