Weights for Aspect-Controlled Neural Argument Generation

dc.contributor.author	Schiller, Benjamin
dc.contributor.author	Daxenberger, Johannes
dc.contributor.author	Gurevych, Iryna
dc.date.accessioned	2020-05-07T15:23:13Z
dc.date.available	2020-05-07T15:23:13Z
dc.date.issued	2020-05
dc.identifier.uri	https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2328
dc.description	This collection includes trained weights for the controlled argument generation models which were fine-tuned on Common-Crawl and Reddit-Comments dumps. For more information, please refer to the paper and the GitHub repository linked in the paper. DISCLAIMER: All weights provided as downloads may be used for research purposes only. The user acknowledges and agrees that the data is provided on an “as-is” basis and that the licensor makes no representations or warranties of any kind.	en_US
dc.language.iso	en	en_US
dc.relation	IsCitedBy;arXiv;2005.00084
dc.rights	In Copyright
dc.rights.uri	https://rightsstatements.org/vocab/InC/1.0/
dc.subject	argument generation	en_US
dc.subject	controlled argument generation	en_US
dc.subject	aspect detection	en_US
dc.title	Weights for Aspect-Controlled Neural Argument Generation	en_US
dc.type	Model	en_US
dc.description.version	1.0	en_US
tud.project	PTJ \| 03VP02540 \| ArgumenText	en_US
tud.project	DFG \| GU798/25-1 \| Offenes Argument-Min	en_US
tud.unit	TUDa