Long document summarization is an important and hard task in the field of natural language processing. A good performance of the long document summarization reveals the model has a decent understanding of the human language. Currently, most researches focus on how to modify the attention mechanism of the transformer to achieve a higher ROUGE score. The study of data pre-processing and post-processing are relatively few. In this paper, we use two pre-processing methods and a post-processing method and analyze the effect of these methods on various long document summarization models.
@article{arxiv.2112.01660,
title = {The Influence of Data Pre-processing and Post-processing on Long Document Summarization},
author = {Xinwei Du and Kailun Dong and Yuchen Zhang and Yongsheng Li and Ruei-Yu Tsay},
journal= {arXiv preprint arXiv:2112.01660},
year = {2021}
}