@inproceedings{miculicich-etal-2019-selecting,
title = "Selecting, Planning, and Rewriting: A Modular Approach for Data-to-Document Generation and Translation",
author = "Miculicich, Lesly and
Marone, Marc and
Hassan, Hany",
editor = "Birch, Alexandra and
Finch, Andrew and
Hayashi, Hiroaki and
Konstas, Ioannis and
Luong, Thang and
Neubig, Graham and
Oda, Yusuke and
Sudoh, Katsuhito",
booktitle = "Proceedings of the 3rd Workshop on Neural Generation and Translation",
month = nov,
year = "2019",
address = "Hong Kong",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-5633",
doi = "10.18653/v1/D19-5633",
pages = "289--296",
abstract = "In this paper, we report our system submissions to all 6 tracks of the WNGT 2019 shared task on Document-Level Generation and Translation. The objective is to generate a textual document from either structured data: generation task, or a document in a different language: translation task. For the translation task, we focused on adapting a large scale system trained on WMT data by fine tuning it on the RotoWire data. For the generation task, we participated with two systems based on a selection and planning model followed by (a) a simple language model generation, and (b) a GPT-2 pre-trained language model approach. The selection and planning module chooses a subset of table records in order, and the language models produce text given such a subset.",
}
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%0 Conference Proceedings
%T Selecting, Planning, and Rewriting: A Modular Approach for Data-to-Document Generation and Translation
%A Miculicich, Lesly
%A Marone, Marc
%A Hassan, Hany
%Y Birch, Alexandra
%Y Finch, Andrew
%Y Hayashi, Hiroaki
%Y Konstas, Ioannis
%Y Luong, Thang
%Y Neubig, Graham
%Y Oda, Yusuke
%Y Sudoh, Katsuhito
%S Proceedings of the 3rd Workshop on Neural Generation and Translation
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong
%F miculicich-etal-2019-selecting
%X In this paper, we report our system submissions to all 6 tracks of the WNGT 2019 shared task on Document-Level Generation and Translation. The objective is to generate a textual document from either structured data: generation task, or a document in a different language: translation task. For the translation task, we focused on adapting a large scale system trained on WMT data by fine tuning it on the RotoWire data. For the generation task, we participated with two systems based on a selection and planning model followed by (a) a simple language model generation, and (b) a GPT-2 pre-trained language model approach. The selection and planning module chooses a subset of table records in order, and the language models produce text given such a subset.
%R 10.18653/v1/D19-5633
%U https://aclanthology.org/D19-5633
%U https://doi.org/10.18653/v1/D19-5633
%P 289-296
Markdown (Informal)
[Selecting, Planning, and Rewriting: A Modular Approach for Data-to-Document Generation and Translation](https://aclanthology.org/D19-5633) (Miculicich et al., NGT 2019)
ACL