This paper presents a comprehensive survey of ChatGPT-related (GPT-3.5 and GPT-4)
research, state-of-the-art large language models (LLM) from the GPT series, and their …

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 …

Language models (LMs) are becoming the foundation for almost all major language
technologies, but their capabilities, limitations, and risks are not well understood. We present …

The quality of texts generated by natural language generation (NLG) systems is hard to
measure automatically. Conventional reference-based metrics, such as BLEU and ROUGE …

Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative impact, these new …

Large language models (LLMs) have shown promise for automatic summarization but the
reasons behind their successes are poorly understood. By conducting a human evaluation …

Generative Artificial Intelligence (AI) has enabled the development of sophisticated models
that are capable of producing high-caliber text, images, and other outputs through the …

The recent success of zero-and few-shot prompting with models like GPT-3 has led to a
paradigm shift in NLP research. In this paper, we study its impact on text summarization …

Recently, the emergence of ChatGPT has attracted wide attention from the computational
linguistics community. Many prior studies have shown that ChatGPT achieves remarkable …

Fine-tuning large pre-trained language models on downstream tasks has become an
important paradigm in NLP. However, common practice fine-tunes all of the parameters in a …