Argument Generation with Retrieval, Planning, and Realization
39704Authors
nan
Abstract
AbstractAutomatic argument generation is an appealing but challenging task. In this paper, we study the specific problem of counter-argument generation, and present a novel framework, CANDELA. It consists of a powerful retrieval system and a novel two-step generation model, where a text planning decoder first decides on the main talking points and a proper language style for each sentence, then a content realization decoder reflects the decisions and constructs an informative paragraph-level argument. Furthermore, our generation model is empowered by a retrieval system indexed with 12 million articles collected from Wikipedia and popular English news media, which provides access to high-quality content with diversity. Automatic evaluation on a large-scale dataset collected from Reddit shows that our model yields significantly higher BLEU, ROUGE, and METEOR scores than the state-of-the-art and non-trivial comparisons. Human evaluation further indicates that our system arguments are more appropriate for refutation and richer in content.
Keywords
Full Content
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 2661–2672 Florence, Italy, July 28 - August 2, 2019. c⃝2019 Association for Computational Linguistics 2661 Argument Generation with Retrieval, Planning, and Realization Xinyu Hua, Zhe Hu, and Lu Wang Khoury College of Computer Sciences Northeastern University Boston, MA 02115 {hua.x, hu.zhe}@husky.neu.edu, luwang@ccs.neu.edu Abstract Automatic argument generation is an appeal- ing but challenging task. In this paper, we study the specific problem of counter- argument generation, and present a novel framework, CANDELA. It consists of a pow- erful retrieval system and a novel two-step generation model, where a text planning de- coder first decides on the main talking points and a proper language style for each sentence, then a content realization decoder reflects the decisions and constructs an informative paragraph-level argument. Furthermore, our generation model is empowered by a retrieval system indexed with 12 million articles col- lected from Wikipedia and popular English news media, which provides access to high- quality content with diversity. Automatic eval- uation on a large-scale dataset collected from Reddit shows that our model yields signifi- cantly higher BLEU, ROUGE, and METEOR scores than the state-of-the-art and non-trivial comparisons. Human evaluation further indi- cates that our system arguments are more ap- propriate for refutation and richer in content. 1 Introduction Counter-argument generation aims to produce ar- guments of a different stance, in order to refute the given proposition on a controversial issue (Toul- min, 1958; Damer, 2012). A system that automati- cally constructs counter-arguments can effectively present alternative perspectives along with asso- ciated evidence and reasoning, and thus facilitate a more comprehensive understanding of compli- cated problems when controversy arises. Nevertheless, constructing persuasive argu- ments is a challenging task, as it requires an appro- priate combination of credible evidence, rigorous logical reasoning, and sometimes emotional ap- peal (Walton et al., 2008; Wachsmuth et al., 2017a; Wang et al., 2017). A sample counter-argument List of exonerated death row inmates... there had been 156 exonerations of prisoners on death row in the United States since 1973... Original post: Death penalty is more rational than life in prison. ...I don't believe murderers and rapists can be successfully integrated... Counter-argument: In theory I agree with you. But in reality we will never have a perfect justice system. Unreliable evidence is used when there is no witnesses, which could result in wrongful convictions. In the US, there had been 156 death row inmates who were exonerated since 1973. If we execute them, we can never undo it. I hope it can change your view. The Grim Facts About Lethal Injection ...Our justice system is a joke and we are asking other people to... The problem of innocence in death penalty cases ...The evidence in death penalty cases is not always very strong. After all, in many murders, there are no surviving witnesses... Source: The New York Times Source: Wikipedia Source: The Wall Street Journal Figure 1: Sample counter-argument for a pro-death penalty statement from Reddit /r/ChangeMyView. The argument consists …
Content truncated to 500 words
Labeled Text
AbstractAutomatic argument generation is an appealing but challenging task. In this paper, we study the specific problem of counter-argument generation, and present a novel framework, CANDELA. It consists of a powerful retrieval system and a novel two-step generation model, where a text planning decoder first decides on the main talking points and a proper language style for each sentence, then a content realization decoder reflects the decisions and constructs an informative paragraph-level argument. Furthermore, our generation model is empowered by a retrieval system indexed with 12 million articles collected from Wikipedia and popular English news media, which provides access to high-quality content with diversity. Automatic evaluation on a large-scale dataset collected from Reddit shows that our model yields significantly higher BLEU, ROUGE, and METEOR scores than the state-of-the-art and non-trivial comparisons. Human evaluation further indicates that our system arguments are more appropriate for refutation and richer in content.
Publication Details
- Paper ID:
- 39704
- Year:
- 2019
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan