@inproceedings{hidey-mckeown-2019-fixed,
title = "Fixed That for You: Generating Contrastive Claims with Semantic Edits",
author = "Hidey, Christopher and
McKeown, Kathy",
editor = "Burstein, Jill and
Doran, Christy and
Solorio, Thamar",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N19-1174",
doi = "10.18653/v1/N19-1174",
pages = "1756--1767",
abstract = "Understanding contrastive opinions is a key component of argument generation. Central to an argument is the claim, a statement that is in dispute. Generating a counter-argument then requires generating a response in contrast to the main claim of the original argument. To generate contrastive claims, we create a corpus of Reddit comment pairs self-labeled by posters using the acronym FTFY (fixed that for you). We then train neural models on these pairs to edit the original claim and produce a new claim with a different view. We demonstrate significant improvement over a sequence-to-sequence baseline in BLEU score and a human evaluation for fluency, coherence, and contrast.",
}
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%0 Conference Proceedings
%T Fixed That for You: Generating Contrastive Claims with Semantic Edits
%A Hidey, Christopher
%A McKeown, Kathy
%Y Burstein, Jill
%Y Doran, Christy
%Y Solorio, Thamar
%S Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota
%F hidey-mckeown-2019-fixed
%X Understanding contrastive opinions is a key component of argument generation. Central to an argument is the claim, a statement that is in dispute. Generating a counter-argument then requires generating a response in contrast to the main claim of the original argument. To generate contrastive claims, we create a corpus of Reddit comment pairs self-labeled by posters using the acronym FTFY (fixed that for you). We then train neural models on these pairs to edit the original claim and produce a new claim with a different view. We demonstrate significant improvement over a sequence-to-sequence baseline in BLEU score and a human evaluation for fluency, coherence, and contrast.
%R 10.18653/v1/N19-1174
%U https://aclanthology.org/N19-1174
%U https://doi.org/10.18653/v1/N19-1174
%P 1756-1767
Markdown (Informal)
[Fixed That for You: Generating Contrastive Claims with Semantic Edits](https://aclanthology.org/N19-1174) (Hidey & McKeown, NAACL 2019)
ACL
- Christopher Hidey and Kathy McKeown. 2019. Fixed That for You: Generating Contrastive Claims with Semantic Edits. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 1756–1767, Minneapolis, Minnesota. Association for Computational Linguistics.