Sequence-to-Sequence Models for Data-to-Text Natural Language Generation: Word- vs. Character-based Processing and Output Diversity

11 October 2018

Papers citing "Sequence-to-Sequence Models for Data-to-Text Natural Language Generation: Word- vs. Character-based Processing and Output Diversity"

6 / 6 papers shown

Title
Innovations in Neural Data-to-text Generation: A Survey Mandar Sharma Ajay K. Gogineni Naren Ramakrishnan 24 10 0 25 Jul 2022
Lexical Features Are More Vulnerable, Syntactic Features Have More Predictive Power Jekaterina Novikova Aparna Balagopalan Ksenia Shkaruta Frank Rudzicz 17 7 0 30 Sep 2019
Evaluating the State-of-the-Art of End-to-End Natural Language Generation: The E2E NLG Challenge Ondrej Dusek Jekaterina Novikova Verena Rieser ELM 21 231 0 23 Jan 2019
OpenNMT: Open-Source Toolkit for Neural Machine Translation Guillaume Klein Yoon Kim Yuntian Deng Jean Senellart Alexander M. Rush 254 1,896 0 10 Jan 2017
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,740 0 26 Sep 2016
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 214 7,923 0 17 Aug 2015