Error syntax aware augmentation of feedback comment generation dataset
December 29, 2022 ยท Declared Dead ยท ๐ International Conference on Natural Language Generation
"No code URL or promise found in abstract"
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Authors
Nikolay Babakov, Maria Lysyuk, Alexander Shvets, Lilya Kazakova, Alexander Panchenko
arXiv ID
2212.14293
Category
cs.CL: Computation & Language
Citations
3
Venue
International Conference on Natural Language Generation
Last Checked
5 months ago
Abstract
This paper presents a solution to the GenChal 2022 shared task dedicated to feedback comment generation for writing learning. In terms of this task given a text with an error and a span of the error, a system generates an explanatory note that helps the writer (language learner) to improve their writing skills. Our solution is based on fine-tuning the T5 model on the initial dataset augmented according to syntactical dependencies of the words located within indicated error span. The solution of our team "nigula" obtained second place according to manual evaluation by the organizers.
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