As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …

This article offers a comprehensive review of the research on Natural Language Generation
(NLG) over the past two decades, especially in relation to data-to-text generation and text-to …

Many real-world applications of language models (LMs), such as writing assistance and
code autocomplete, involve human-LM interaction. However, most benchmarks are non …

Chatbots are increasingly becoming important gateways to digital services and information—
taken up within domains such as customer service, health, education, and work support …

Evaluating natural language generation (NLG) is a vital but challenging problem in artificial
intelligence. Traditional evaluation metrics mainly capturing content (eg n-gram) overlap …

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 …

Recommender systems exploit interaction history to estimate user preference, having been
heavily used in a wide range of industry applications. However, static recommendation …

In recent years, conversational agents (CAs) have become ubiquitous and are a presence in
our daily routines. It seems that the technology has finally ripened to advance the use of CAs …

For chatbots to be broadly adopted by users, it is critical that they are experienced as useful
and pleasurable. While there is an emerging body of research concerning user uptake and …

Large language models distill broad knowledge from text corpora. However, they can be
inconsistent when it comes to completing user specified tasks. This issue can be addressed …