Wenke Huang

Batman: Benign Knowledge Alignment Through Malicious Null Space in Federated Backdoor Attack CVPR 2026 DAWN: Distributed LLM Multi-Agent Workflow Synthesis AAAI 2026 Divide, Conquer and Unite: Hierarchical Style-Recalibrated Prototype Alignment for Federated Medical Segmentation AAAI 2026 Domain-Aware Suppression and Aggregation for Federated DG ReID AAAI 2026 EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models CVPR 2026 FedBPrompt: Federated Domain Generalization Person Re-Identification via Body Distribution Aware Visual Prompts CVPR 2026 Federated Context-Aware Personalized Recommendation AAAI 2026 FedHarmony: Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning CVPR 2026 FedSDR: Federated Graph Learning with Structural Noise Detection and Reconstruction CVPR 2026 Probing Semantic Insensitivity for Inference-Time Backdoor Defense in Multimodal Large Language Model AAAI 2026 RGMP: Recurrent Geometric-prior Multimodal Policy for Generalizable Humanoid Robot Manipulation AAAI 2026 SafeGRPO: Self-Rewarded Multimodal Safety Alignment via Rule-Governed Policy Optimization CVPR 2026 Towards Robust Text-Attributed Federated Graph Learning: Multimodal Threats and Defense AAAI 2026 S^2FGL: Spatial Spectral Federated Graph Learning ICML 2025 An Empirical Study of Federated Prompt Learning for Vision Language Model IJCAI 2025 Be Confident: Uncovering Overfitting in MLLM Multi-Task Tuning ICML 2025 Catch Your Emotion: Sharpening Emotion Perception in Multimodal Large Language Models ICML 2025 Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning ICML 2025 EAGLES: Towards Effective, Efficient, and Economical Federated Graph Learning via Unified Sparsification ICML 2025 EMOE: Modality-Specific Enhanced Dynamic Emotion Experts CVPR 2025 Energy-based Backdoor Defense Against Federated Graph Learning ICLR 2025 Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation ICML 2025 Federated Recommendation with Explicitly Encoding Item Bias AAAI 2025 FedPHA: Federated Prompt Learning for Heterogeneous Client Adaptation ICML 2025 FedSPA: Generalizable Federated Graph Learning under Homophily Heterogeneity CVPR 2025 Geometric Knowledge-Guided Localized Global Distribution Alignment for Federated Learning CVPR 2025 GHOST: Generalizable One-Shot Federated Graph Learning with Proxy-Based Topology Knowledge Retention ICML 2025 Label-Free Backdoor Attacks in Vertical Federated Learning AAAI 2025 Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning ICML 2025 LoRASculpt: Sculpting LoRA for Harmonizing General and Specialized Knowledge in Multimodal Large Language Models CVPR 2025 Pixel-wise Divide and Conquer for Federated Vessel Segmentation IJCAI 2025 Splitting with Importance-aware Updating for Heterogeneous Federated Learning with Large Language Models ICML 2025 SPMC: Self-Purifying Federated Backdoor Defense via Margin Contribution ICML 2025 Unsupervised Visible-Infrared Person Re-identification under Unpaired Settings ICCV 2025 Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity CVPR 2024 FedAS: Bridging Inconsistency in Personalized Federated Learning CVPR 2024 Federated Graph Learning under Domain Shift with Generalizable Prototypes AAAI 2024 FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference NeurIPS 2024 Fisher Calibration for Backdoor-Robust Heterogeneous Federated Learning ECCV 2024 Parameter Disparities Dissection for Backdoor Defense in Heterogeneous Federated Learning NeurIPS 2024 S3GCL: Spectral, Swift, Spatial Graph Contrastive Learning ICML 2024 Self-Driven Entropy Aggregation for Byzantine-Robust Heterogeneous Federated Learning ICML 2024 Dynamic Personalized Federated Learning with Adaptive Differential Privacy NeurIPS 2023 Federated Graph Semantic and Structural Learning IJCAI 2023 Rethinking Federated Learning With Domain Shift: A Prototype View CVPR 2023 Learn From Others and Be Yourself in Heterogeneous Federated Learning CVPR 2022