Automatic knowledge graph construction aims at manufacturing structured human
knowledge. To this end, much effort has historically been spent extracting informative fact …

Remote sensing technology in the new era gradually need a new scientific paradigm driven
by big data and knowledge. However, in the current research, the use of existing knowledge …

A taxonomy represents a hierarchically structured knowledge graph that forms the
infrastructure for various downstream applications, including recommender systems, web …

Large multi-modal models (LMMs) have demonstrated promising intelligence owing to the
rapid development of pre-training techniques. However, their fine-grained cross-modal …

In the context of COVID-19, numerous people present their opinions through social
networks. It is thus highly desired to conduct sentiment analysis towards COVID-19 tweets to …

Noun compounds are abundant in various languages and their interpretations have been
applied in a wide range of NLP tasks. However, most existing work only uses relation …

Recently, prompt-based learning has shown impressive performance on various natural
language processing tasks in few-shot scenarios. The previous study of knowledge probing …

To achieve state-of-the-art performance, one still needs to train NER models on large-scale,
high-quality annotated data, an asset that is both costly and time-intensive to accumulate. In …

In recent years, with the rapid growth of Artificial Intelligence (AI) and the Internet of Things
(IoT), the question answering systems for human-machine interaction based on deep …

摘要上下位关系是自然语言处理领域中的重要概念, 用于描述概念之间的从属关系.
上下位关系的精准预测, 有助于挖掘概念之间的内在层次结构, 是构建大规模语义网络 …