Da-Wei Zhou

papers

1,142

total citations

papers (13)

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning

CVPR 2024arXiv

116

citations

Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration

NEURIPS 2023arXiv

citations

Parrot: Multilingual Visual Instruction Tuning

ICML 2025arXiv

citations

MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning

AAAI 2025arXiv

citations

Task-Agnostic Guided Feature Expansion for Class-Incremental Learning

CVPR 2025arXiv

citations

Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning

CVPR 2025arXiv

citations

Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts

ICML 2025arXiv

citations

External Knowledge Injection for CLIP-Based Class-Incremental Learning

ICCV 2025arXiv

citations

Integrating Task-Specific and Universal Adapters for Pre-Trained Model-based Class-Incremental Learning

ICCV 2025arXiv

citations

Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning

ICML 2024

citations

Da-Wei Zhou

papers (13)

FOSTER: Feature Boosting and Compression for Class-Incremental Learning

Forward Compatible Few-Shot Class-Incremental Learning

Learning Placeholders for Open-Set Recognition

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning

Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration

Parrot: Multilingual Visual Instruction Tuning

MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning

Task-Agnostic Guided Feature Expansion for Class-Incremental Learning

Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning

Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts

External Knowledge Injection for CLIP-Based Class-Incremental Learning

Integrating Task-Specific and Universal Adapters for Pre-Trained Model-based Class-Incremental Learning

Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning

papers (13)

FOSTER: Feature Boosting and Compression for Class-Incremental Learning

Forward Compatible Few-Shot Class-Incremental Learning

Learning Placeholders for Open-Set Recognition

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning

Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration

Parrot: Multilingual Visual Instruction Tuning

MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning

Task-Agnostic Guided Feature Expansion for Class-Incremental Learning

Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning

Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts

External Knowledge Injection for CLIP-Based Class-Incremental Learning

Integrating Task-Specific and Universal Adapters for Pre-Trained Model-based Class-Incremental Learning

Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning