continual learning

Revisiting Neural Networks for Continual Learning: An Architectural Perspective IJCAI 2024 Robust Feature Learning and Global Variance-Driven Classifier Alignment for Long-Tail Class Incremental Learning WACV 2024 SAFE: Slow and Fast Parameter-Efficient Tuning for Continual Learning with Pre-Trained Models NeurIPS 2024 Saliency-driven Experience Replay for Continual Learning NeurIPS 2024 SAPT: A Shared Attention Framework for Parameter-Efficient Continual Learning of Large Language Models ACL 2024 Scalable Language Model with Generalized Continual Learning ICLR 2024 Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing ICLR 2024 SEEKR: Selective Attention-Guided Knowledge Retention for Continual Learning of Large Language Models EMNLP 2024 Self-generated Replay Memories for Continual Neural Machine Translation NAACL 2024 Semantically-Shifted Incremental Adapter-Tuning is A Continual ViTransformer CVPR 2024 Semantic Segmentation in Multiple Adverse Weather Conditions with Domain Knowledge Retention AAAI 2024 SharpSeq: Empowering Continual Event Detection through Sharpness-Aware Sequential-task Learning NAACL 2024 SimCS: Simulation for Domain Incremental Online Continual Segmentation AAAI 2024 Solving the Catastrophic Forgetting Problem in Generalized Category Discovery CVPR 2024 Sparse Diffusion Policy: A Sparse, Reusable, and Flexible Policy for Robot Learning CoRL 2024 Stabilizing Zero-Shot Prediction: A Novel Antidote to Forgetting in Continual Vision-Language Tasks NeurIPS 2024 STAF: Pushing the Boundaries of Test-Time Adaptation towards Practical Noise Scenarios COLING 2024 Steering Prototypes With Prompt-Tuning for Rehearsal-Free Continual Learning WACV 2024 Summarizing Stream Data for Memory-Constrained Online Continual Learning AAAI 2024 TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models ICLR 2024 Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning ICML 2024 Task Confusion and Catastrophic Forgetting in Class-Incremental Learning: A Mathematical Framework for Discriminative and Generative Modelings NeurIPS 2024 Task-Free Continual Generation and Representation Learning via Dynamic Expansionable Memory Cluster AAAI 2024 Task-Free Dynamic Sparse Vision Transformer for Continual Learning AAAI 2024 Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning NeurIPS 2024