  We describe the task of sentence expansion and enhancement, in which a
sentence provided by a human is expanded in some creative way. The expansion
should be understandable, believably grammatical, and optimally
meaning-preserving. Sentence expansion and enhancement may serve as an
authoring tool, or integrate in dynamic media, conversational agents, or
variegated advertising.
  We implement a neural sentence expander trained on sentence compressions
generated from a corpus of modern fiction. We modify an MLE objective to
support the task by focusing on new words, and decode at test time with
controlled curve-like novelty sampling. We run our sentence expander on
sentences provided by human subjects and have humans evaluate these expansions.
We show that, although the generation methods are inferior to professional
human writers, they are comparable to, and as well liked as, our subjects'
original input sentences, and preferred over baselines.
