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RSTGen : imbuing fine-grained interpretable control into long-form text generators
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Adewoyin, Rilwan A., Dutta, Ritabrata and He, Yulan (2022) RSTGen : imbuing fine-grained interpretable control into long-form text generators. In: NAACL 2022 : Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Seattle, Washington, 10-15 Jul 2022. Published in: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies pp. 1822-1835. doi:10.18653/v1/2022.naacl-main.133
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WRAP-RSTGen-imbuing-fine-grained-interpretable-control-long-form-text-generators-Adewoyin-2022.pdf - Accepted Version - Requires a PDF viewer. Download (756Kb) | Preview |
Official URL: https://doi.org/10.18653/v1/2022.naacl-main.133
Abstract
In this paper, we study the task of improving the cohesion and coherence of long-form text generated by language models.To this end, we propose RSTGen, a framework that utilises Rhetorical Structure Theory (RST), a classical language theory, to control the discourse structure, semantics and topics of generated text. Firstly, we demonstrate our model’s ability to control structural discourse and semantic features of generated text in open generation evaluation. Then we experiment on the two challenging long-form text tasks of argument generation and story generation. Evaluation using automated metrics and a metric with high correlation to human evaluation, shows that our model performs competitively against existing models, while offering significantly more controls over generated text than alternative methods.
| Item Type: | Conference Item (Paper) | ||||||||||||
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| Subjects: | P Language and Literature > P Philology. Linguistics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||||||
| Library of Congress Subject Headings (LCSH): | Natural language processing (Computer science) , Speech processing systems, Text processing (Computer science), Computational linguistics | ||||||||||||
| Journal or Publication Title: | Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies | ||||||||||||
| Publisher: | Association for Computational Linguistics | ||||||||||||
| Official Date: | 2022 | ||||||||||||
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| Page Range: | pp. 1822-1835 | ||||||||||||
| DOI: | 10.18653/v1/2022.naacl-main.133 | ||||||||||||
| Status: | Peer Reviewed | ||||||||||||
| Publication Status: | Published | ||||||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
| Date of first compliant deposit: | 25 May 2022 | ||||||||||||
| Date of first compliant Open Access: | 25 May 2022 | ||||||||||||
| RIOXX Funder/Project Grant: |
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| Conference Paper Type: | Paper | ||||||||||||
| Title of Event: | NAACL 2022 : Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies | ||||||||||||
| Type of Event: | Conference | ||||||||||||
| Location of Event: | Seattle, Washington | ||||||||||||
| Date(s) of Event: | 10-15 Jul 2022 | ||||||||||||
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