Generating Long Financial Report using Conditional Variational Autoencoders with Knowledge Distillation

Yunpeng Ren, Ziao Wang, Yiyuan Wang, Xiaofeng Zhang

Abstract: Automatically generating financial report from a piece of news is quite a challenging task. Apparently, the difficulty of this task lies in the lack of sufficient background knowledge to effectively generate long financial report. To address this issue, this paper proposes the conditional variational autoencoders (CVAE) based approach which distills external knowledge from a corpus of news-report data. Experimental results demonstrate that the proposed approach could achieve the SOTA performance.