What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific Presentations

Liu, Dongqi, Whitehouse, Chenxi, Yu, Xi, Mahon, Louis, Saxena, Rohit, Zhao, Zheng, Qiu, Yifu, Lapata, Mirella, Demberg, Vera

arXiv.org Artificial Intelligence 

Transforming recorded videos into concise and accurate textual summaries is a growing challenge in multimodal learning. This paper introduces VISTA, a dataset specifically designed for video-to-text summarization in scientific domains. VISTA contains 18,599 recorded AI conference presentations paired with their corresponding paper abstracts. We benchmark the performance of state-of-the-art large models and apply a plan-based framework to better capture the structured nature of abstracts. Both human and automated evaluations confirm that explicit planning enhances summary quality and factual consistency. However, a considerable gap remains between models and human performance, highlighting the challenges of scientific video summarization.