# IndoSum: A New Benchmark Dataset for Indonesian Text Summarization

arXiv: https://arxiv.org/abs/1810.05334 · HTML: https://mlsanity.com/paper/1810.05334/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Oct 2018.

## Built on by (most cited first, 14 of 14)

- [The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset](https://mlsanity.com/paper/2303.03915/) (2023)
- [A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methods](https://mlsanity.com/paper/2403.02901/) (2024)
- [One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia](https://mlsanity.com/paper/2203.13357/) (2022)
- [IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation](https://mlsanity.com/paper/2104.08200/) (2021)
- [NusaCrowd: Open Source Initiative for Indonesian NLP Resources](https://mlsanity.com/paper/2212.09648/) (2022)
- [IndoNLI: A Natural Language Inference Dataset for Indonesian](https://mlsanity.com/paper/2110.14566/) (2021)
- [SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 13 Languages](https://mlsanity.com/paper/2402.08638/) (2024)
- [Komodo: A Linguistic Expedition into Indonesia's Regional Languages](https://mlsanity.com/paper/2403.09362/) (2024)
- [The State and Fate of Summarization Datasets: A Survey](https://mlsanity.com/paper/2411.04585/) (2024)
- [SailCompass: Towards Reproducible and Robust Evaluation for Southeast Asian Languages](https://mlsanity.com/paper/2412.01186/) (2024)
- [Low-Resource Clickbait Spoiling for Indonesian via Question Answering](https://mlsanity.com/paper/2310.08085/) (2023)
- [Investigating Text Shortening Strategy in BERT: Truncation vs Summarization](https://mlsanity.com/paper/2403.12799/) (2024)
- [Simple Hack for Transformers against Heavy Long-Text Classification on a Time- and Memory-Limited GPU Service](https://mlsanity.com/paper/2403.12563/) (2024)
- [Structure-Preserving Document-Level Data Augmentation via Discourse Parsing](https://mlsanity.com/paper/2610.19497/) (2026)

## Abstract (arXiv)

Automatic text summarization is generally considered as a challenging task in the NLP community. One of the challenges is the publicly available and large dataset that is relatively rare and difficult to construct. The problem is even worse for low-resource languages such as Indonesian. In this paper, we present IndoSum, a new benchmark dataset for Indonesian text summarization. The dataset consists of news articles and manually constructed summaries. Notably, the dataset is almost 200x larger than the previous Indonesian summarization dataset of the same domain. We evaluated various extractive summarization approaches and obtained encouraging results which demonstrate the usefulness of the dataset and provide baselines for future research. The code and the dataset are available online under permissive licenses.