The prediction results for our NAACL 2021 paper "Enhancing Factual Consistency of Abstractive Summarization" are available at https://drive.google.com/file/d/1pDk6b0KlS_er0_vr32-Y01cLasTtNZMW/view?usp=sharing.
This includes the produced summary from all the systems (UniLM, BottomUp, TConvS2S, FASum) and the corresponding corrected summaries by the model FC, on the test set of CNN/DailyMail and XSUM. It also contains the reference summary and the corresponding articles in the test set.
If you use our prediction results, please cite our paper:
Enhancing Factual Consistency of Abstractive Summarization
Chenguang Zhu, William Hinthorn, Ruochen Xu, Qingkai Zeng, Michael Zeng, Xuedong Huang, Meng Jiang
North American Chapter of the Association for Computational Linguistics (NAACL), Mexico City, Mexico, 2021.
#Summaries in CNN's test set: 11,490
#Summaries in XSUM's test set: 11,301