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DOI: 10.4230/OASIcs.SLATE.2023.4
Generating and Ranking Distractors for Multiple-Choice Questions in Portuguese

Authors: Hugo Gonçalo Oliveira, Igor Caetano, Renato Matos, and Hugo Amaro

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)

Abstract
In the process of multiple-choice question generation, different methods are often considered for distractor acquisition, as an attempt to cover as many questions as possible. Some, however, result in many candidate distractors of variable quality, while only three or four are necessary. We implement some distractor generation methods for Portuguese and propose their combination and ranking with language models. Experimentation results confirm that this increases both coverage and suitability of the selected distractors.
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Hugo Gonçalo Oliveira, Igor Caetano, Renato Matos, and Hugo Amaro. Generating and Ranking Distractors for Multiple-Choice Questions in Portuguese. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 4:1-4:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{goncalooliveira_et_al:OASIcs.SLATE.2023.4,
  author =	{Gon\c{c}alo Oliveira, Hugo and Caetano, Igor and Matos, Renato and Amaro, Hugo},
  title =	{{Generating and Ranking Distractors for Multiple-Choice Questions in Portuguese}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{4:1--4:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.4},
  URN =		{urn:nbn:de:0030-drops-185185},
  doi =		{10.4230/OASIcs.SLATE.2023.4},
  annote =	{Keywords: Multiple-Choice Questions, Distractor Generation, Language Models}
}
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