Yixiong Zou

papers

159

total citations

papers (12)

Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting Mitigation

NEURIPS 2022arXiv

citations

Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation

ICML 2025arXiv

citations

Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation

ICML 2025arXiv

citations

Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling

AAAI 2024arXiv

citations

Revisiting Pool-based Prompt Learning for Few-shot Class-incremental Learning

ICCV 2025arXiv

citations

Reconstruction Target Matters in Masked Image Modeling for Cross-Domain Few-Shot Learning

AAAI 2025arXiv

citations

Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization

NEURIPS 2025arXiv

citations

Random Registers for Cross-Domain Few-Shot Learning

ICML 2025arXiv

citations

Cross-Category Subjectivity Generalization for Style-Adaptive Sketch Re-ID

ICCV 2025

citations

Yixiong Zou

papers (12)

Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting Mitigation

Flatten Long-Range Loss Landscapes for Cross-Domain Few-Shot Learning

Compositional Few-Shot Class-Incremental Learning

The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation

Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation

Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation

Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling

Revisiting Pool-based Prompt Learning for Few-shot Class-incremental Learning

Reconstruction Target Matters in Masked Image Modeling for Cross-Domain Few-Shot Learning

Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization

Random Registers for Cross-Domain Few-Shot Learning

Cross-Category Subjectivity Generalization for Style-Adaptive Sketch Re-ID

papers (12)

Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting Mitigation

Flatten Long-Range Loss Landscapes for Cross-Domain Few-Shot Learning

Compositional Few-Shot Class-Incremental Learning

The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation

Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation

Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation

Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling

Revisiting Pool-based Prompt Learning for Few-shot Class-incremental Learning

Reconstruction Target Matters in Masked Image Modeling for Cross-Domain Few-Shot Learning

Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization

Random Registers for Cross-Domain Few-Shot Learning

Cross-Category Subjectivity Generalization for Style-Adaptive Sketch Re-ID