We introduce Texygen, a benchmarking platform to support research on open-domain text generation models. Texygen has not only implemented a majority of text generation models, but also covered a set of metrics that evaluate the diversity, the quality and the consistency of the generated texts. The Texygen platform could help standardize the research on text generation and facilitate the sharing of fine-tuned open-source implementations among researchers for their work. As a consequence, this would help in improving the reproductivity and reliability of future research work in text generation.
@article{arxiv.1802.01886,
title = {Texygen: A Benchmarking Platform for Text Generation Models},
author = {Yaoming Zhu and Sidi Lu and Lei Zheng and Jiaxian Guo and Weinan Zhang and Jun Wang and Yong Yu},
journal= {arXiv preprint arXiv:1802.01886},
year = {2018}
}