Controllable Text Generation (CTG) is an emerging area in the field of natural language
generation (NLG). It is regarded as crucial for the development of advanced text generation …

Quality improvement methods are essential to gathering high-quality crowdsourced data,
both for research and industry applications. A popular and broadly applicable method is task …

Human evaluations are typically considered the gold standard in natural language
generation, but as models' fluency improves, how well can evaluators detect and judge …

The paper surveys evaluation methods of natural language generation (NLG) systems that
have been developed in the last few years. We group NLG evaluation methods into three …

We systematically study a wide variety of generative models spanning semantically-diverse
image datasets to understand and improve the feature extractors and metrics used to …

Human language is colored by a broad range of topics, but existing text analysis tools only
focus on a small number of them. We present Empath, a tool that can generate and validate …

Crowdsourcing provides a scalable and efficient way to construct labeled datasets for
training machine learning systems. However, creating comprehensive label guidelines for …

Recent research on creativity support tools (CST) adopts artificial intelligence (AI) that
leverages big data and computational capabilities to facilitate creative work. Our work aims …

Social media has quickly risen to prominence as a news source, yet lingering doubts remain
about its ability to spread rumor and misinformation. Systematically studying this …

Errors and biases are earning algorithms increasingly malignant reputations in society. A
central challenge is that algorithms must bridge the gap between high-level policy and on …