Before revision:  To support automatic evaluation, we also conducted human evaluation and received higher scores relative to both baseline and reference summaries .
After revision:  To support automatic evaluation, we also conducted human evaluation and received higher scores relative to reference summaries. Stemming from our experimental results, we first argue the intrinsic characteristics of the CNN/DM dataset, the progress of pre-trained language models, and their ability to generalize on the training data. Finally, we share our insights into the model-generated summaries and presents our thought on learning methods for abstractive summarization .