Fixed length summarization aims at generating summaries with a preset number of words or characters. Most recent researches incorporate length information with word embeddings as the input to the recurrent decoding unit, causing a compromise between length controllability and summary quality. In this work, we present an effective length controlling unit Length Attention (LenAtten) to break this trade-off. Experimental results show that LenAtten not only brings improvements in length controllability and ROGUE scores but also has great generalization ability. In the task of generating a summary with the target length, our model is 732 times better than the best-performing length controllable summarizer in length controllability on the CNN/Daily Mail dataset.
@article{arxiv.2106.00316,
title = {LenAtten: An Effective Length Controlling Unit For Text Summarization},
author = {Zhongyi Yu and Zhenghao Wu and Hao Zheng and Zhe XuanYuan and Jefferson Fong and Weifeng Su},
journal= {arXiv preprint arXiv:2106.00316},
year = {2021}
}