Before revision:   Experimental results show our proposed approach achieves significant gains on several multilingual QA benchmarks , reducing the gap between zero-shot and supervised performance of  QA models on various languages.
After revision:  Human evaluations indicate the majority of such samples are grammatically correct and sensible. Experimental results show our proposed approach achieves significant gains on several multilingual QA benchmarks , reducing the gap between zero-shot and supervised performance of QA models on various languages.