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 …

The forthcoming generation of wireless technology, 6G, promises a revolutionary leap
beyond traditional data-centric services. It aims to usher in an era of ubiquitous intelligent …

Recent years have witnessed the resurgence of knowledge engineering which is featured
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …

Abstract Vision-language (V+ L) pretraining models have achieved great success in
supporting multimedia applications by understanding the alignments between images and …

Large language models have shown astonishing performance on a wide range of reasoning
tasks. In this paper, we investigate whether they could reason about real-world events and …

We propose a new task, Text2Mol, to retrieve molecules using natural language descriptions
as queries. Natural language and molecules encode information in very different ways …

Scene graph generation (SGG) aims to abstract an image into a graph structure, by
representing objects as graph nodes and their relations as labeled edges. However, two …

To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant
biomedical knowledge in scientific literature to understand the disease mechanism and …

Event extraction (EE) is a crucial research task for promptly apprehending event information
from massive textual data. With the rapid development of deep learning, EE based on deep …

Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are
also an essential kind of knowledge in the world, which trigger the spring up of event-centric …