# Fiction Sentence Expansion and Enhancement via Focused Objective and Novelty Curve Sampling

arXiv: https://arxiv.org/abs/1912.00698 · HTML: https://mlsanity.com/paper/1912.00698/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Dec 2019.

## Built on by (most cited first, 4 of 4)

- [Inspiration through Observation: Demonstrating the Influence of Automatically Generated Text on Creative Writing](https://mlsanity.com/paper/2107.04007/) (2021)
- [A Survey of Natural Language Generation](https://mlsanity.com/paper/2112.11739/) (2021)
- [LongStory: Coherent, Complete and Length Controlled Long story Generation](https://mlsanity.com/paper/2311.15208/) (2023)
- [Task-Oriented Paraphrase Analytics](https://mlsanity.com/paper/2403.17564/) (2024)

## Abstract (arXiv)

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.