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Yao-Chung Fan

3 accepted papers

2024

Enhancing Distractor Generation for Multiple-Choice Questions with Retrieval Augmented Pretraining and Knowledge Graph Integration

ACL 2024findings

In this paper, we tackle the task of distractor generation (DG) for multiple-choice questions. Our study introduces two key designs. First, we propose the concept of retrieval augmented pretraining, which involves refining the language model pretraining to align it more closely with the downstream t…

Cited by 4SourcePDFScholar
2023

Distractor Generation based on Text2Text Language Models with Pseudo Kullback-Leibler Divergence Regulation

ACL 2023findings

In this paper, we address the task of cloze-style multiple choice question (MCQs) distractor generation. Our study is featured by the following designs. First, we propose to formulate the cloze distractor generation as a Text2Text task. Second, we propose pseudo Kullback-Leibler Divergence for regul…

Cited by 10SourcePDFScholar
2022

CDGP: Automatic Cloze Distractor Generation based on Pre-trained Language Model

EMNLP 2022finding

Manually designing cloze test consumes enormous time and efforts. The major challenge lies in wrong option (distractor) selection. Having carefully-design distractors improves the effectiveness of learner ability assessment. As a result, the idea of automatically generating cloze distractor is motiv…