Visual Entailment

Visual entailment (VE) is a multimodal reasoning task that assesses whether an image semantically implies a given textual statement. Current research focuses on improving VE models' accuracy and robustness, particularly by exploring advanced architectures that leverage object-level alignment within images and text, and by incorporating uncertainty modeling and hierarchical alignment strategies. This work is significant because accurate VE systems are crucial for various applications, including fact verification, image captioning, and more generally, improving the reliability and understanding of information presented in image-text formats.