Sensitivity-Aware Visual Parameter-Efficient Fine-Tuning
灵敏度感知视觉参数高效微调
On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion
关于开放世界测试时训练的鲁棒性：动态原型扩展的自我训练
Boosting Novel Category Discovery over Domains with Soft Contrastive Learning and all in One Classifier
通过软对比学习和多合一分类器促进领域的新类别发现
A Soft Nearest-Neighbor Framework for Continual Semi-Supervised Learning
持续半监督学习的软最近邻框架
GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation
GraphEcho：用于超声心动图视频分割的图驱动无监督域适应
ViperGPT: Visual Inference via Python Execution for Reasoning
ViperGPT：通过 Python 执行进行视觉推理以进行推理
Improved Visual Fine-Tuning with Natural Language Supervision
通过自然语言监督改进视觉微调
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