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 …

Abstract Evaluation practices in natural language generation (NLG) have many known flaws,
but improved evaluation approaches are rarely widely adopted. This issue has become …

Text summarization aims at compressing long documents into a shorter form that conveys
the most important parts of the original document. Despite increased interest in the …

Human assessment remains the most trusted form of evaluation in NLG, but highly diverse
approaches and a proliferation of different quality criteria used by researchers make it …

The majority of NLG evaluation relies on automatic metrics, such as BLEU. In this paper, we
motivate the need for novel, system-and data-independent automatic evaluation methods …

Currently, there is little agreement as to how Natural Language Generation (NLG) systems
should be evaluated, with a particularly high degree of variation in the way that human …

This paper provides a comprehensive analysis of the first shared task on End-to-End Natural
Language Generation (NLG) and identifies avenues for future research based on the results …

Human evaluation for natural language generation (NLG) often suffers from inconsistent
user ratings. While previous research tends to attribute this problem to individual user …

As transparency becomes key for robotics and AI, it will be necessary to evaluate the
methods through which transparency is provided, including automatically generated natural …

Recent studies have exploited advanced generative language models to generate Natural
Language Explanations (NLE) for why a certain text could be hateful. We propose the Chain …