← Learning Types
Machine Learning › Learning Types ›

Continual Learning

1895 directly classified papers

Papers per year

Papers

Progressive Homeostatic and Plastic Prompt Tuning for Audio-Visual Multi-Task Incremental Learning ICCV 2025
Enhancing Embodied Object Detection with Spatial Feature Memory WACV 2025
Modality-Incremental Learning with Disjoint Relevance Mapping Networks for Image-Based Semantic Segmentation WACV 2025
SAMULE: Self-Learning Agents Enhanced by Multi-level Reflection EMNLP 2025
Dynamic Expert Specialization: Towards Catastrophic Forgetting-Free Multi-Domain MoE Adaptation EMNLP 2025
Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios ICCV 2025
Efficient Deformable Convolutional Prompt for Continual Test-Time Adaptation in Medical Image Segmentation AAAI 2025
Revisiting Pool-based Prompt Learning for Few-shot Class-incremental Learning ICCV 2025
A Tiny Change, A Giant Leap: Long-Tailed Class-Incremental Learning via Geometric Prototype Alignment ICCV 2025
Instruction-Grounded Visual Projectors for Continual Learning of Generative Vision-Language Models ICCV 2025
SMoLoRA: Exploring and Defying Dual Catastrophic Forgetting in Continual Visual Instruction Tuning ICCV 2025
GCD: Advancing Vision-Language Models for Incremental Object Detection via Global Alignment and Correspondence Distillation AAAI 2025
Continual Multiple Instance Learning with Enhanced Localization for Histopathological Whole Slide Image Analysis ICCV 2025
Queryable Prototype Multiple Instance Learning with Vision-Language Models for Incremental Whole Slide Image Classification AAAI 2025
Multi-View Incremental Learning with Structured Hebbian Plasticity for Enhanced Fusion Efficiency AAAI 2025
Domain-adaptative Continual Learning for Low-resource Tasks: Evaluation on Nepali COLING 2025
Joint Diffusion Models in Continual Learning ICCV 2025
DualCP: Rehearsal-Free Domain-Incremental Learning via Dual-Level Concept Prototype AAAI 2025
NLPART at SemEval-2025 Task 4: Forgetting is harder than Learning ACL 2025
Bring Your Own Knowledge: A Survey of Methods for LLM Knowledge Expansion ACL 2025
Federated Continuous Category Discovery and Learning ICCV 2025
UNLEARN Efficient Removal of Knowledge in Large Language Models NAACL 2025
Flexi-FSCIL: Adaptive Knowledge Retention for Breaking the Stability-Plasticity Dilemma in Few-Shot Class-Incremental Learning ICCV 2025
Multilingual Continual Learning using Attention Distillation COLING 2025
Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code COLING 2025