# CMHG: A Dataset and Benchmark for Headline Generation of Minority Languages in China

arXiv: https://arxiv.org/abs/2509.09990 · HTML: https://mlsanity.com/paper/2509.09990/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 6 references that are in the map.
- First posted on arXiv 12 Sep 2025.

## Builds on (most cited first, 2 of 2)

- [CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages](https://mlsanity.com/paper/2309.09400/) (2023)
- [Perplexed by Quality: A Perplexity-based Method for Adult and Harmful Content Detection in Multilingual Heterogeneous Web Data](https://mlsanity.com/paper/2212.10440/) (2022)

## Built on by (most cited first, 3 of 3)

- [Reinforcement Learning with Semantic Rewards Enables Low-Resource Language Expansion without Alignment Tax](https://mlsanity.com/paper/2605.14366/) (2026)
- [LaoBench: A Large-Scale Multidimensional Lao Benchmark for Large Language Models](https://mlsanity.com/paper/2511.11334/) (2025)
- [Towards the Roof of the World: NLP Progress in Tibetan Languages](https://mlsanity.com/paper/2610.13398/) (2026)

## Abstract (arXiv)

Minority languages in China, such as Tibetan, Uyghur, and Traditional Mongolian, face significant challenges due to their unique writing systems, which differ from international standards. This discrepancy has led to a severe lack of relevant corpora, particularly for supervised tasks like headline generation. To address this gap, we introduce a novel dataset, Chinese Minority Headline Generation (CMHG), which includes 100,000 entries for Tibetan, and 50,000 entries each for Uyghur and Mongolian, specifically curated for headline generation tasks. Additionally, we propose a high-quality test set annotated by native speakers, designed to serve as a benchmark for future research in this domain. We hope this dataset will become a valuable resource for advancing headline generation in Chinese minority languages and contribute to the development of related benchmarks.