Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …

We present $\textbf {MolT5} $$-$ a self-supervised learning framework for pretraining
models on a vast amount of unlabeled natural language text and molecule strings. $\textbf …

Abstract recommendation, and marketing services. Extensive efforts have been made to
conquer the cross-modal retrieval problem in the general domain. When it comes to E …

We propose Visual News Captioner, an entity-aware model for the task of news image
captioning. We also introduce Visual News, a large-scale benchmark consisting of more …

Current image captioning systems perform at a merely descriptive level, essentially
enumerating the objects in the scene and their relations. Humans, on the contrary, interpret …

Recently, the burgeoning demands for captioning-related applications have inspired great
endeavors in the remote sensing community. However, current benchmark datasets are …

We propose an end-to-end model which generates captions for images embedded in news
articles. News images present two key challenges: they rely on real-world knowledge …

Entity-aware image captioning aims to describe named entities and events related to the
image by utilizing the background knowledge in the associated article. This task remains …

Have you ever looked at a painting and wondered what is the story behind it? This work
presents a framework to bring art closer to people by generating comprehensive …

The image caption is a technology that enables us to understand the contents and generate
descriptive text, of images using machines. With the development of deep learning, means …