LVT和FRE用于Transformer模型的实验
Experiments with LVT and FRE for Transformer model
摘要：
在本文中，我们尝试将大词汇量技巧和丰富的词汇编码应用于文本摘要的Transformer模型。我们无法获得比类似的基于RNN的序列到序列模型更好的结果，所以我们尝试了更多的模型来找出是什么改善了结果，是什么恶化了结果。
英文摘要：
In this paper, we experiment with Large Vocabulary Trick and Feature-rich encoding applied to the Transformer model for Text Summarization. We could not achieve better results, than the analogous RNN-based sequence-to-sequence model, so we tried more models to find out, what improves the results and what deteriorates them.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
