Abstract: At present, Machine Reading Comprehension (MRC) has achieved good success. However, many researches show that MRC models still have some problems in the robustness in terms of over-sensitivity and over-stability. In order to solve these problems, a multi-task MRC model oriented to robustness enhancement is proposed to strengthen the model's ability to understand the passage and the problem. Specifically, in the multi-task learning method, answer extraction is the main task, and the judgment of evidence sentences and the classification of question are auxiliary tasks, which realizes information sharing between these tasks. The experimental results on the robustness test sets show that the proposed model's performance has a significant improvement compared with the baseline models.

Key words: robustness, multi-task learning, machine reading comprehension