End-To-End Neural Text Classification For Tibetan

As a minority language, Tibetan has received relatively little attention in the field of natural language processing (NLP), especially in current various neural network models. In this paper, we investigate three end-to-end neural models for Tibetan text classification. The experimental results show that the end-to-end models outperform the traditional Tibetan text classification methods. The dataset and codes are available on https://github.com/FudanNLP/Tibetan-Classification.