What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific Presentations
Dongqi Liu, Chenxi Whitehouse, Xi Yu, Louis Mahon, Rohit Saxena, Zheng Zhao, Yifu Qiu, Mirella Lapata, Vera Demberg
摘要
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-totext summarization. The project information is available at https://dongqi.me/projects/VISTA .
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper2
- Cut to the Chase: Training-free Multimodal Summarization via Chain-of-EventsXiaoxing You, Qiang Huang, Lingyu Li, Xiaojun Chang 等CVPR 2026 · 被引用 4 次
- KCVR: Knowledge-Centric Video Reconstruction for Structured Pedagogical Summarization via Dynamic Graph PlanningJingjiang Liu, Jia Zhu, Hanghui Guo, Weijie Shi 等ACL 2026
它引用的顶会 Paper40
- BERTScore: Evaluating Text Generation with BERTTianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger 等ICLR 2020 · 被引用 8,443 次
- QLoRA: Efficient Finetuning of Quantized LLMsTim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke ZettlemoyerNeurIPS 2023 · 被引用 5,863 次
- MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsPan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu 等ICLR 2024 · 被引用 1,472 次
- Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language ModelsMuhammad Maaz, Hanoona Abdul Rasheed, Salman Khan, Fahad KhanACL 2024 · 被引用 279 次
- When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric MemoriesAlex Mallen, Akari Asai, Victor Zhong, Rajarshi Das 等ACL 2023 · 被引用 233 次
相关 Paper
- V2Xum-LLM: Cross-Modal Video Summarization with Temporal Prompt Instruction TuningHang Hua, Yunlong Tang, Chenliang Xu, Jiebo LuoAAAI 2025 · 被引用 61 次
- Scaling Up Video Summarization Pretraining with Large Language ModelsDawit Mureja Argaw, Seunghyun Yoon, Fabian Caba Heilbron, Hanieh Deilamsalehy 等CVPR 2024
- VISTA: A Test-Time Self-Improving Video Generation AgentDo Xuan Long, Xingchen Wan, Hootan Nakhost, Chen-Yu Lee 等CVPR 2026 · 被引用 30 次
- VISTA: Enhancing Long-Duration and High-Resolution Video Understanding by Video Spatiotemporal AugmentationWeiming Ren, Huan Yang, Jie Min, Cong Wei 等CVPR 2025
- SD-VSum: A Method and Dataset for Script-Driven Video SummarizationManolis Mylonas, Evlampios Apostolidis, Vasileios MezarisACM MM 2025 · 被引用 2 次
