XBMU-TibSum: A Tibetan Text Summarization Dataset for Large Language Model Fine-Tuning

ScienceDB 2026 Dataset Open access

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Authors: dan rui lei, He Xiangzhen, 孟祥鹤 Meng Xianghe, Ouyang Xu, Huangzijian, Shi Shibiao, Zhu Haotian, Hao Jingbin, Wang Xiang, Jiang Wenhao, Du Tingting
DOI: 10.57760/sciencedb.j00001.01727
Cited by: 0

Abstract

A Tibetan long-text summarization dataset constructed for large language model (LLM) fine-tuning. It contains 9,979 pairs of structured instruction fine-tuning samples. The dataset utilizes LLMs to reconstruct high-information-density summary labels and extracts core entities to serve as semantic anchors.

Publication details

Journal / source
ScienceDB
Publication date
24 April 2026
Language
ZH
Document type
Dataset