SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 31–40 of 41 papers

TitleStatusHype
BERT-based distractor generation for Swedish reading comprehension questions using a small-scale datasetCode0
Automatic Distractor Generation for Multiple Choice Questions in Standard Tests—0
Better Distractions: Transformer-based Distractor Generation and Multiple Choice Question Filtering—0
Knowledge-Driven Distractor Generation for Cloze-style Multiple Choice Questions—0
Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension—0
Good, Better, Best: Textual Distractors Generation for Multiple-Choice Visual Question Answering via Reinforcement Learning—0
Equipping Educational Applications with Domain Knowledge—0
Difficulty-aware Distractor Generation for Gap-Fill Items—0
Distractor Generation for Multiple Choice Questions Using Learning to RankCode0
Distractor Generation for Chinese Fill-in-the-blank Items—0
Show:102550
← PrevPage 4 of 5Next →

No leaderboard results yet.