As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …

This monograph surveys vision-language pre-training (VLP) methods for multimodal
intelligence that have been developed in the last few years. We group these approaches …

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

In recent years, we have witnessed significant performance boost in the image captioning
task based on vision-language pre-training (VLP). Scale is believed to be an important factor …

Connecting Vision and Language plays an essential role in Generative Intelligence. For this
reason, large research efforts have been devoted to image captioning, ie describing images …

This article offers a comprehensive review of the research on Natural Language Generation
(NLG) over the past two decades, especially in relation to data-to-text generation and text-to …

In this work, we investigate the task of text-to-image (T2I) synthesis under the abstract-to-
intricate setting, ie, generating intricate visual content from simple abstract text prompts …

Image-text matching plays a critical role in bridging the vision and language, and great
progress has been made by exploiting the global alignment between image and sentence …

Transformer-based architectures represent the state of the art in sequence modeling tasks
like machine translation and language understanding. Their applicability to multi-modal …

Today's scene graph generation (SGG) task is still far from practical, mainly due to the
severe training bias, eg, collapsing diverse" human walk on/sit on/lay on beach" into" human …