Technical report on Conversational Question Answering

24 Sep 2019 Ying Ju Fubang Zhao Shijie Chen Bowen Zheng Xuefeng Yang Yunfeng Liu

Conversational Question Answering is a challenging task since it requires understanding of conversational history. In this project, we propose a new system RoBERTa + AT +KD, which involves rationale tagging multi-task, adversarial training, knowledge distillation and a linguistic post-process strategy... (read more)

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