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Tag-Set-Sequence Learning for Generating Question-Answer Pairs
Cheng Zhang, Jie Wang
Transformer-based QG models can generate question-answer pairs (QAPs) with high qualities, but may also generate silly questions for certain texts. We present a new method called t…
Downstream Transformer Generation of Question-Answer Pairs with Preprocessing and Postprocessing Pipelines
Cheng Zhang, Hao Zhang, Jie Wang
We present a system called TP3 to perform a downstream task of transformers on generating question-answer pairs (QAPs) from a given article. TP3 first finetunes pretrained transfor…
Generating Adequate Distractors for Multiple-Choice Questions
Cheng Zhang, Yicheng Sun, Hejia Chen +1
This paper presents a novel approach to automatic generation of adequate distractors for a given question-answer pair (QAP) generated from a given article to form an adequate multi…
Meta Sequence Learning for Generating Adequate Question-Answer Pairs
Cheng Zhang, Jie Wang
Creating multiple-choice questions to assess reading comprehension of a given article involves generating question-answer pairs (QAPs) on the main points of the document. We presen…
Generating an Overview Report over Many Documents
Jingwen Wang, Hao Zhang, Cheng Zhang +3
How to efficiently generate an accurate, well-structured overview report (ORPT) over thousands of related documents is challenging. A well-structured ORPT consists of sections of m…