This paper presents the setup and results of the second edition of the BioLaySumm shared task on the Lay Summarisation of Biomedical Research Articles, hosted at the BioNLP Workshop at ACL 2024. In this task edition, we aim to build on the first edition's success by further increasing research interest in this important task and encouraging participants to explore novel approaches that will help advance the state-of-the-art. Encouragingly, we found research interest in the task to be high, with this edition of the task attracting a total of 53 participating teams, a significant increase in engagement from the previous edition. Overall, our results show that a broad range of innovative approaches were adopted by task participants, with a predictable shift towards the use of Large Language Models (LLMs).

本研究解决了生物医学研究文章通俗摘要方面的兴趣和参与度不足的问题，强调了持续推动该领域研究的重要性。通过举办BioLaySumm共享任务，吸引了53个参与团队，展示了众多创新方法的应用，特别是大型语言模型的使用。该工作的主要发现表明，增加的参与度和多样的技术方法将有助于提升生物医学研究的可访问性。

2024年BioLaySumm共享任务关于生物医学研究文章的通俗摘要概述