Papers by Zi Chai

2 papers
Asking the Crowd: Question Analysis, Evaluation and Generation for Open Discussion on Online Forums (P19-1)

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Challenge: Existing work on teaching machines to ask questions focused on generating fixed answers.
Approach: They propose a model to generate open-answered questions from real-world news for open discussion . they analyze how language use affects the number of answers .
Outcome: The proposed model generates questions with higher quality than most text generation methods.
Learning to Ask More: Semi-Autoregressive Sequential Question Generation under Dual-Graph Interaction (2020.acl-main)

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Challenge: Existing approaches to Question Generation (QG) only capture limited context dependencies due to information omission and coreference between questions.
Approach: They propose to generate questions in a semi-autoregressive way to produce interconnected questions when there is a sequence of answers.
Outcome: The proposed model significantly outperforms previous models on a dataset containing 81.9K questions.

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