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

Sentiment analysis is one of the traditional well-known tasks in Natural Language
Processing (NLP) research. In recent years, Pre-trained Models (PMs) have become one of …

Prompt engineering is a critical technique in the field of natural language processing that
involves designing and optimizing the prompts used to input information into models, aiming …

The capability of Large Language Models (LLMs) like ChatGPT to comprehend user intent
and provide reasonable responses has made them extremely popular lately. In this paper …

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 …

Event extraction has gained considerable interest due to its wide-ranging applications.
However, recent studies draw attention to evaluation issues, suggesting that reported scores …

The EAE task extracts a structured event record from an event text. Most existing approaches
train the EAE model on each dataset independently and ignore the overlap knowledge …

Event argument extraction (EAE) aims to identify the arguments of a given event, and
classify the roles that those arguments play. Due to high data demands of training EAE …

Event extraction (EE) is a crucial task aiming at extracting events from texts, which includes
two subtasks: event detection (ED) and event argument extraction (EAE). In this paper, we …

Abstract Out-of-distribution (OOD) detection, a fundamental task vexing real-world
applications, has attracted growing attention in the NLP community. Recently fine-tuning …