Generating Long Financial Report using Conditional Variational Autoencoders with Knowledge Distillation
FOS: Computer and information sciences
Computer Science - Machine Learning
01 natural sciences
Machine Learning (cs.LG)
0105 earth and related environmental sciences
DOI:
10.1609/aaai.v35i18.17936
Publication Date:
2022-09-08T20:38:19Z
AUTHORS (4)
ABSTRACT
Automatically generating financial report from a piece of news is quite challenging task. Apparently, the difficulty this task lies in lack sufficient background knowledge to effectively generate long report. To address issue, paper proposes conditional variational autoencoders (CVAE) based approach which distills external corpus news-report data. Experimental results demonstrate that proposed could achieve SOTA performance.
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