Deep learning has emerged as a powerful tool in various domains, revolutionising machine
learning research. However, one persistent challenge is the scarcity of labelled training …

Over the last few years, large language models (LLMs) have emerged as the most important
breakthroughs in natural language processing (NLP) that fundamentally transform research …

A key technology for the development of large language models (LLMs) involves instruction
tuning that helps align the models' responses with human expectations to realize impressive …

In this work, we focus on Cross-Lingual Event Detection where a model is trained on data
from a source language but its performance is evaluated on data from a second, target …

In this paper, we address the Event Detection task under a zero-shot cross-lingual setting
where a model is trained on a source language but evaluated on a distinct target language …

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 …

Machine learning algorithms have had a profound impact on the field of computer science
over the past few decades. The performance of these algorithms heavily depends on the …

Event Detection (ED) is the task of identifying and classifying trigger words of event mentions
in text. Despite considerable research efforts in recent years for English text, the task of ED …

Event Extraction (EE) is one of the fundamental tasks in Information Extraction (IE) that aims
to recognize event mentions and their arguments (ie, participants) from text. Due to its …

Extracting entities, events, event arguments, and relations (ie, task instances) from text
represents four main challenging tasks in information extraction (IE), which have been …