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 …

The task of resolving repeated objects in natural languages is known as coreference
resolution, and it is an important part of modern natural language processing. It is classified …

Information extraction suffers from its varying targets, heterogeneous structures, and
demand-specific schemas. In this paper, we propose a unified text-to-structure generation …

A wide variety of NLP applications, such as machine translation, summarization, and dialog,
involve text generation. One major challenge for these applications is how to evaluate …

Universally modeling all typical information extraction tasks (UIE) with one generative
language model (GLM) has revealed great potential by the latest study, where various IE …

Event extraction is challenging due to the complex structure of event records and the
semantic gap between text and event. Traditional methods usually extract event records by …

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 …

Event extraction has long been treated as a sentence-level task in the IE community. We
argue that this setting does not match human information-seeking behavior and leads to …

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

The problem of event extraction requires detecting the event trigger and extracting its
corresponding arguments. Existing work in event argument extraction typically relies heavily …