# TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks

arXiv: https://arxiv.org/abs/1906.01351 · HTML: https://mlsanity.com/paper/1906.01351/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Jun 2019.

## Built on by (most cited first, 20 of 20)

- [A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methods](https://mlsanity.com/paper/2403.02901/) (2024)
- [DOC2PPT: Automatic Presentation Slides Generation from Scientific Documents](https://mlsanity.com/paper/2101.11796/) (2021)
- [FactKB: Generalizable Factuality Evaluation using Language Models Enhanced with Factual Knowledge](https://mlsanity.com/paper/2305.08281/) (2023)
- [Automated scholarly paper review: Concepts, technologies, and challenges](https://mlsanity.com/paper/2111.07533/) (2021)
- [LimGen: Probing the LLMs for Generating Suggestive Limitations of Research Papers](https://mlsanity.com/paper/2403.15529/) (2024)
- [CiteSum: Citation Text-guided Scientific Extreme Summarization and Domain Adaptation with Limited Supervision](https://mlsanity.com/paper/2205.06207/) (2022)
- [What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific Presentations](https://mlsanity.com/paper/2502.08279/) (2025)
- [PosterSum: A Multimodal Benchmark for Scientific Poster Summarization](https://mlsanity.com/paper/2502.17540/) (2025)
- [Extractive Research Slide Generation Using Windowed Labeling Ranking](https://mlsanity.com/paper/2106.03246/) (2021)
- [Knowledge-Centric Templatic Views of Documents](https://mlsanity.com/paper/2401.06945/) (2024)
- [Summaformers @ LaySumm 20, LongSumm 20](https://mlsanity.com/paper/2101.03553/) (2021)
- [Citance-Contextualized Summarization of Scientific Papers](https://mlsanity.com/paper/2311.02408/) (2023)
- [M3AV: A Multimodal, Multigenre, and Multipurpose Audio-Visual Academic Lecture Dataset](https://mlsanity.com/paper/2403.14168/) (2024)
- [An Exploration of Post-Editing Effectiveness in Text Summarization](https://mlsanity.com/paper/2206.06383/) (2022)
- [The State and Fate of Summarization Datasets: A Survey](https://mlsanity.com/paper/2411.04585/) (2024)
- [NUTSHELL: A Dataset for Abstract Generation from Scientific Talks](https://mlsanity.com/paper/2502.16942/) (2025)
- [SciBERTSUM: Extractive Summarization for Scientific Documents](https://mlsanity.com/paper/2201.08495/) (2022)
- [SuMe: A Dataset Towards Summarizing Biomedical Mechanisms](https://mlsanity.com/paper/2205.04652/) (2022)
- [SPEC: Summary Preference Decomposition for Low-Resource Abstractive Summarization](https://mlsanity.com/paper/2303.14011/) (2023)
- [Community-Driven Comprehensive Scientific Paper Summarization: Insight from cvpaper.challenge](https://mlsanity.com/paper/2203.09109/) (2022)

## Abstract (arXiv)

Currently, no large-scale training data is available for the task of scientific paper summarization. In this paper, we propose a novel method that automatically generates summaries for scientific papers, by utilizing videos of talks at scientific conferences. We hypothesize that such talks constitute a coherent and concise description of the papers' content, and can form the basis for good summaries. We collected 1716 papers and their corresponding videos, and created a dataset of paper summaries. A model trained on this dataset achieves similar performance as models trained on a dataset of summaries created manually. In addition, we validated the quality of our summaries by human experts.