mlsanityData to 7 Oct 2026

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

arXiv 2502.08279 ↗First posted 12 Feb 2025cs.CL cs.AI cs.CVcited by 11

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Abstract (arXiv)

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 our dataset. This study aims to pave the way for future research on scientific video-to-text summarization.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 61 of its 97 references that are in the map. First posted on arXiv 12 Feb 2025.

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61 of 97 references.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 7.

11 papers.