Texar: A Modularized, Versatile, and Extensible Toolbox for Text Generation

Zhiting Hu, Zichao Yang, Tiancheng Zhao, Haoran Shi, Junxian He, Di Wang, Xuezhe Ma, Zhengzhong Liu, Xiaodan Liang, Lianhui Qin, Devendra Singh Chaplot, Bowen Tan, Xingjiang Yu, Eric Xing


Abstract
We introduce Texar, an open-source toolkit aiming to support the broad set of text generation tasks. Different from many existing toolkits that are specialized for specific applications (e.g., neural machine translation), Texar is designed to be highly flexible and versatile. This is achieved by abstracting the common patterns underlying the diverse tasks and methodologies, creating a library of highly reusable modules and functionalities, and enabling arbitrary model architectures and various algorithmic paradigms. The features make Texar particularly suitable for technique sharing and generalization across different text generation applications. The toolkit emphasizes heavily on extensibility and modularized system design, so that components can be freely plugged in or swapped out. We conduct extensive experiments and case studies to demonstrate the use and advantage of the toolkit.
Anthology ID:
W18-2503
Volume:
Proceedings of Workshop for NLP Open Source Software (NLP-OSS)
Month:
July
Year:
2018
Address:
Melbourne, Australia
Venues:
ACL | NLPOSS | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
13–22
Language:
URL:
https://www.aclweb.org/anthology/W18-2503
DOI:
10.18653/v1/W18-2503
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-2503.pdf