Before revision:  To further improve the performances of the question answering model, we propose a reinforcement learning method that rewards generated questions that improves the extraction learning. Experimental results showed that our model outperforms the state-of-the-art  pretrained language models on standard question answering benchmarks, and reaches the state-of-the-art performance under the zero-shot learning setting.
After revision:  To further improve the performances of the question answering model, we propose a reinforcement learning technique to reward generating high-quality questions and to improve the answer extraction model's performance. Experiment results show that REGEX outperforms the state-of-the-art pretrained language models on standard question answering benchmarks, and reaches the state-of-the-art performance under the zero-shot learning setting.