Abstract Domain Generalization (DG) aims to develop a versatile model capable of
performing well on unseen target domains. Recent advancements in pre-trained Visual …

The ability to accurately comprehend natural language instructions and navigate to the
target location is essential for an embodied agent. Such agents are typically required to …

Abstract Domain generalization (DG) aims to avoid the performance degradation of the
model when the distribution shift between the limited training data and unseen test data …

Deep learning methods often struggle with the domain shift problem, leading to poor
generalization on out-of-domain (OOD) data. To address the problem, domain …

Learning a robust vision model despite large distribution shift is essential for model
deployment in real-world settings. Especially, domain generalization (DG) algorithm aims to …

Domain Generalization (DG) aims to learn a model from multiple source domains to achieve
satisfactory performance on unseen target domains. Recent works introduce CLIP to DG …