neural networks

Semantic Noise Matters for Neural Natural Language Generation

Neural natural language generation (NNLG) systems are known for their pathological outputs, i.e. generating text which is unrelated to the input specification. In this paper, we show the impact of semantic noise on state-of-theart NNLG models which …

Noise and Neural Natural Language GenerationRubbish in, Rubbish out?

At this workshop we highlighted several sources of noise for neural NLG (semantic, typographic, and grammatical) before presenting the impact of semantic noise on the quality of NNLG (in a preview of our INLG paper) and how these different kinds of errors impact human evaluations of perceived text quality.