# An Overview of Indian Language Datasets used for Text Summarization

arXiv: https://arxiv.org/abs/2203.16127 · HTML: https://mlsanity.com/paper/2203.16127/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 56 references that are in the map.
- First posted on arXiv 30 Mar 2022.

## Builds on (most cited first, 14 of 14)

- [Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization](https://mlsanity.com/paper/1808.08745/) (2018)
- [Teaching Machines to Read and Comprehend](https://mlsanity.com/paper/1506.03340/) (2015)
- [Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model](https://mlsanity.com/paper/1906.01749/) (2019)
- [A Neural Attention Model for Abstractive Sentence Summarization](https://mlsanity.com/paper/1509.00685/) (2015)
- [XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages](https://mlsanity.com/paper/2106.13822/) (2021)
- [Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies](https://mlsanity.com/paper/1804.11283/) (2018)
- [Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting](https://mlsanity.com/paper/1805.11080/) (2018)
- [BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization](https://mlsanity.com/paper/1906.03741/) (2019)
- [MLSUM: The Multilingual Summarization Corpus](https://mlsanity.com/paper/2004.14900/) (2020)
- [Neural Extractive Text Summarization with Syntactic Compression](https://mlsanity.com/paper/1902.00863/) (2019)
- [iNLTK: Natural Language Toolkit for Indic Languages](https://mlsanity.com/paper/2009.12534/) (2020)
- [A Multilingual Parallel Corpora Collection Effort for Indian Languages](https://mlsanity.com/paper/2007.07691/) (2020)
- [Unsupervised Abstractive Summarization of Bengali Text Documents](https://mlsanity.com/paper/2102.04490/) (2021)
- [Neural Abstractive Text Summarizer for Telugu Language](https://mlsanity.com/paper/2101.07120/) (2021)

## Built on by (most cited first, 1 of 1)

- [PMIndiaSum: Multilingual and Cross-lingual Headline Summarization for Languages in India](https://mlsanity.com/paper/2305.08828/) (2023)

## Abstract (arXiv)

In this paper, we survey Text Summarization (TS) datasets in Indian Languages (ILs), which are also low-resource languages (LRLs). We seek to answer one primary question: is the pool of Indian Language Text Summarization (ILTS) dataset growing or is there a resource poverty? To an-swer the primary question, we pose two sub-questions that we seek about ILTS datasets: first, what characteristics: format and domain do ILTS datasets have? Second, how different are those characteristics of ILTS datasets from high-resource languages (HRLs) particularly English. We focus on datasets reported in published ILTS research works during 2012-2022. The survey of ILTS and English datasets reveals two similarities and one contrast. The two similarities are: first, the domain of dataset commonly is news (Hermann et al., 2015). The second similarity is the format of the dataset which is both extractive and abstractive. The contrast is in how the research in dataset development has progressed. ILs face a slow speed of development and public release of datasets as compared with English. We argue that the relatively lower number of ILTS datasets is because of two reasons: first, absence of a dedicated forum for developing TS tools and resources; and second, lack of shareable standard datasets in the public domain.