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Distractor Generation

Given a passage, a question, and an answer phrase, the goal of distractor generation (DG) is to generate context-related wrong options (i.e., distractor) for multiple-choice questions (MCQ).

Papers

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Showing 1–10 of 41 papers

TitleStatusHype
ZmBART: An Unsupervised Cross-lingual Transfer Framework for Language GenerationCode1
Generating Distractors for Reading Comprehension Questions from Real ExaminationsCode1
EduQG: A Multi-format Multiple Choice Dataset for the Educational DomainCode1
Quiz-Style Question Generation for News StoriesCode1
A BERT-based Distractor Generation Scheme with Multi-tasking and Negative Answer Training StrategiesCode1
BRAINTEASER: Lateral Thinking Puzzles for Large Language ModelsCode1
CDGP: Automatic Cloze Distractor Generation based on Pre-trained Language ModelCode1
A BERT-based Distractor Generation Scheme with Multi-tasking and Negative Answer Training Strategies.Code1
Distractor Generation for Multiple Choice Questions Using Learning to RankCode0
BERT-based distractor generation for Swedish reading comprehension questions using a small-scale datasetCode0
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