Wenchao Xu

papers

746

total citations

papers (16)

Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching

ECCV 2024arXiv

citations

Non-exemplar Online Class-Incremental Continual Learning via Dual-Prototype Self-Augment and Refinement

AAAI 2024arXiv

citations

ProCC: Progressive Cross-Primitive Compatibility for Open-World Compositional Zero-Shot Learning

AAAI 2024arXiv

citations

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization

ICML 2024arXiv

citations

Knowledge-Aware Parameter Coaching for Personalized Federated Learning

AAAI 2024

citations

Boosting Fine-Grained Visual Anomaly Detection with Coarse-Knowledge-Aware Adversarial Learning

AAAI 2025arXiv

citations

Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection

ECCV 2024arXiv

citations

DaFKD: Domain-Aware Federated Knowledge Distillation

CVPR 2023

citations

SwapPrompt: Test-Time Prompt Adaptation for Vision-Language Models

NEURIPS 2023

citations

BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach

ICML 2025

citations

Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data

ICML 2024

citations

Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models

ICML 2024

citations

C2KD: Bridging the Modality Gap for Cross-Modal Knowledge Distillation

CVPR 2024

citations

Wenchao Xu

papers (16)

Layer-Wised Model Aggregation for Personalized Federated Learning

Parameterized Knowledge Transfer for Personalized Federated Learning

PMR: Prototypical Modal Rebalance for Multimodal Learning

Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching

Non-exemplar Online Class-Incremental Continual Learning via Dual-Prototype Self-Augment and Refinement

ProCC: Progressive Cross-Primitive Compatibility for Open-World Compositional Zero-Shot Learning

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization

Knowledge-Aware Parameter Coaching for Personalized Federated Learning

Boosting Fine-Grained Visual Anomaly Detection with Coarse-Knowledge-Aware Adversarial Learning

Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection

DaFKD: Domain-Aware Federated Knowledge Distillation

SwapPrompt: Test-Time Prompt Adaptation for Vision-Language Models

BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach

Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data

Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models

C2KD: Bridging the Modality Gap for Cross-Modal Knowledge Distillation

papers (16)

Layer-Wised Model Aggregation for Personalized Federated Learning

Parameterized Knowledge Transfer for Personalized Federated Learning

PMR: Prototypical Modal Rebalance for Multimodal Learning

Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching

Non-exemplar Online Class-Incremental Continual Learning via Dual-Prototype Self-Augment and Refinement

ProCC: Progressive Cross-Primitive Compatibility for Open-World Compositional Zero-Shot Learning

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization

Knowledge-Aware Parameter Coaching for Personalized Federated Learning

Boosting Fine-Grained Visual Anomaly Detection with Coarse-Knowledge-Aware Adversarial Learning

Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection

DaFKD: Domain-Aware Federated Knowledge Distillation

SwapPrompt: Test-Time Prompt Adaptation for Vision-Language Models

BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach

Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data

Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models

C2KD: Bridging the Modality Gap for Cross-Modal Knowledge Distillation