hidden - assigned and confirmed by the Study Dept.
Date of registration:
17.07.2019
Date of assignment:
17.07.2019
Confirmed by Study dept. on:
28.11.2019
Guidelines
Current neural NLG methods are quite hard to control, the generation typically proceeds in a language model style. The outputs often do not contain all content required by the input specification, or contain additional, irrelevant (hallucinated) content. This in effect excludes neural NLG from deployment in production systems. This project will address the reliability problem and explore novel, controllable NLG architectures. A possible extension can focus on the style of generated texts, such as generating outputs with specific personality traits.