# Extractive Research Slide Generation Using Windowed Labeling Ranking

arXiv: https://arxiv.org/abs/2106.03246 · HTML: https://mlsanity.com/paper/2106.03246/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 22 references that are in the map.
- First posted on arXiv 6 Jun 2021.

## Builds on (most cited first, 7 of 7)

- [Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond](https://mlsanity.com/paper/1602.06023/) (2016)
- [SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents](https://mlsanity.com/paper/1611.04230/) (2016)
- [ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks](https://mlsanity.com/paper/1909.01716/) (2019)
- [Extractive Summarization of Long Documents by Combining Global and Local Context](https://mlsanity.com/paper/1909.08089/) (2019)
- [Variations of the Similarity Function of TextRank for Automated Summarization](https://mlsanity.com/paper/1602.03606/) (2016)
- [TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks](https://mlsanity.com/paper/1906.01351/) (2019)
- [A Hierarchical Structured Self-Attentive Model for Extractive Document Summarization (HSSAS)](https://mlsanity.com/paper/1805.07799/) (2018)

## Built on by (most cited first, 7 of 7)

- [TextAtlas5M: A Large-scale Dataset for Dense Text Image Generation](https://mlsanity.com/paper/2502.07870/) (2025)
- [Leopard: A Vision Language Model For Text-Rich Multi-Image Tasks](https://mlsanity.com/paper/2410.01744/) (2024)
- [A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis](https://mlsanity.com/paper/2301.08826/) (2023)
- [SlideSpawn: An Automatic Slides Generation System for Research Publications](https://mlsanity.com/paper/2411.17719/) (2024)
- [SlideBot: A Multi-Agent Framework for Generating Informative, Reliable, Multi-Modal Presentations](https://mlsanity.com/paper/2511.09804/) (2025)
- [SciBERTSUM: Extractive Summarization for Scientific Documents](https://mlsanity.com/paper/2201.08495/) (2022)
- [AgentXRay: White-Boxing Agentic Systems via Workflow Reconstruction](https://mlsanity.com/paper/2602.05353/) (2026)

## Abstract (arXiv)

Presentation slides describing the content of scientific and technical papers are an efficient and effective way to present that work. However, manually generating presentation slides is labor intensive. We propose a method to automatically generate slides for scientific papers based on a corpus of 5000 paper-slide pairs compiled from conference proceedings websites. The sentence labeling module of our method is based on SummaRuNNer, a neural sequence model for extractive summarization. Instead of ranking sentences based on semantic similarities in the whole document, our algorithm measures importance and novelty of sentences by combining semantic and lexical features within a sentence window. Our method outperforms several baseline methods including SummaRuNNer by a significant margin in terms of ROUGE score.