CMMQC: Cascaded Multi-Model Quality Control for Unsupervised Data-to-Text Generation
Author:
Affiliation:
1. Pazhou Lab,Guangzhou,China
2. China Unicom Digital Intelligence Medical Technology Co. Ltd.,Guangzhou,China
Funder
National Science and Technology Major Project
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10649807/10649898/10650876.pdf?arnumber=10650876
Reference34 articles.
1. A Survey of Controllable Text Generation Using Transformer-based Pre-trained Language Models
2. A Survey on Neural Data-to-Text Generation
3. Biomedical Data-to-Text Generation via Fine-Tuning Transformers
4. Learning with Contrastive Examples for Data-to-Text Generation
5. Sumtime-meteo: Parallel corpus of naturally occurring forecast texts and weather data;Sripada,2008
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