WushuQA: A Chinese Martial Arts Question-Answering Dataset for Large Language Model Fine-Tuning

WushuQA is a question-answering dataset designed for instruction fine-tuning of large language models (LLMs) in the domain of Chinese martial arts (武术/Wushu).Background & Motivation: Chinese martial arts feature a vast and intricate knowledge system with highly specialized terminology and complex lineage structures. General-purpose LLMs consistently perform poorly in this domain — confusing styles, misattributing techniques, and giving vague or incorrect explanations of core concepts.

The root cause is a near-total absence of high-quality martial arts text in standard training corpora.Scale: Built upon 1,056 source texts (~2.8 million Chinese characters) drawn from six authoritative sources — including the Wushu Management Center of the General Administration of Sport of China, the Chinese Wushu Association, the International Wushu Federation, Wikipedia, and Baidu Baike — plus one specialized martial arts website, the dataset yields 14,380 high-quality QA pairs in JSONL format.