"The Paradigm Shift in Event Extraction: An In-Depth Overview with Large Language Models," by Dung-Cam Quang, Vinh Q. Vo, Dr. Xuan-Bach Le and Assoc. Prof. Tho Quan, was published at IEA/AIE 2026 in Kuala Lumpur, Malaysia, July 2026. Large language models have moved event extraction forward considerably — a long-standing information extraction task that has already passed through rule-based systems, classical machine learning and deep learning. This survey organises LLM-based methods around two strategies: using LLMs for data augmentation, and using prompting or fine-tuning to tackle the task directly. Unlike earlier surveys, it gives real weight to datasets, covering resources across English, Chinese and Vietnamese, with attention to domain-specific settings and annotation scope. The paper closes with a critical reading of current challenges and a set of directions worth pursuing. Paper: https://lexuanbach.github.io/publication/IEA2026d.pdf DOI: https://doi.org/10.1007/978-981-92-2885-0_6