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Texygen: A Benchmarking Platform for Text Generation Models

Zhu, Y; Lu, S; Zheng, L; Guo, J; Zhang, W; Wang, J; Yu, Y; (2018) Texygen: A Benchmarking Platform for Text Generation Models. In: Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR '18). (pp. pp. 1097-1100). ACM: New York (NY), USA. Green open access

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Abstract

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 improve the reproductivity and reliability of future research work in text generation.

Type: Proceedings paper
Title: Texygen: A Benchmarking Platform for Text Generation Models
Event: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval
Location: Ann Arbor (MI), USA
Dates: 8th-12th July 2018
ISBN-13: 978-1-4503-5657-2
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3209978.3210080
Publisher version: https://dx.doi.org/10.1145/3209978.3210080
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Text Generation, Benchamarking, Evaluation Metrics
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10066104
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