Abstract Information Extraction (IE) aims to extract structural knowledge from plain natural
language texts. Recently, generative Large Language Models (LLMs) have demonstrated …

Generative Knowledge Graph Construction (KGC) refers to those methods that leverage the
sequence-to-sequence framework for building knowledge graphs, which is flexible and can …

ChatGPT has stimulated the research boom in the field of large language models. In this
paper, we assess the capabilities of ChatGPT from four perspectives including Performance …

We consider event extraction in a generative manner with template-based conditional
generation. Although there is a rising trend of casting the task of event extraction as a …

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 …

As a core task and an important link in the fields of natural language understanding and
information retrieval, information extraction (IE) can structure and semanticize unstructured …

Few-shot Learning (FSL) is aimed to make predictions based on a limited number of
samples. Structured data such as knowledge graphs and ontology libraries has been …

Prompt learning approaches have made waves in natural language processing by inducing
better few-shot performance while they still follow a parametric-based learning paradigm; …

We present a study on leveraging multilingual pre-trained generative language models for
zero-shot cross-lingual event argument extraction (EAE). By formulating EAE as a language …

Event trigger detection, entity mention recognition, event argument extraction, and relation
extraction are the four important tasks in information extraction that have been performed …