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 …

The rapid development of Large Language Models (LLMs) demonstrates remarkable
multilingual capabilities in natural language processing, attracting global attention in both …

Like humans, large language models (LLMs) do not always generate the best output on their
first try. Motivated by how humans refine their written text, we introduce Self-Refine, an …

Pretrained language models (PLMs) have demonstrated remarkable performance in various
natural language processing tasks: Unidirectional PLMs (eg, GPT) are well known for their …

Recent work has presented intriguing results examining the knowledge contained in
language models (LMs) by having the LM fill in the blanks of prompts such as “Obama is a …

Event extraction (EE) is a crucial information extraction task that aims to extract event
information in texts. Previous methods for EE typically model it as a classification task, which …

Chatbots' growing popularity has brought new challenges to HCI, having changed the
patterns of human interactions with computers. The increasing need to approximate …

Adversarial attacks and backdoor attacks are two common security threats that hang over
deep learning. Both of them harness task-irrelevant features of data in their implementation …

Recent studies have revealed the intriguing few-shot learning ability of pretrained language
models (PLMs): They can quickly adapt to a new task when fine-tuned on a small amount of …

Text style transfer is an important task in natural language generation, which aims to control
certain attributes in the generated text, such as politeness, emotion, humor, and many …