SemEval 2022 Task

SemEval 2024 encompassed a series of shared tasks focused on advancing natural language processing (NLP), particularly in challenging areas like commonsense reasoning, biomedical text understanding, and machine-generated text detection. Research heavily utilized large language models (LLMs) such as BERT, RoBERTa, and various others, often incorporating techniques like chain-of-thought prompting, data augmentation, and in-context learning to improve performance on diverse tasks. These advancements contribute to a broader understanding of LLM capabilities and limitations, with implications for applications ranging from clinical decision support to combating misinformation.