Over the last several years, the field of natural language processing has been propelled
forward by an explosion in the use of deep learning models. This article provides a brief …

There are enormous enthusiasm and concerns in applying large language models (LLMs) to
healthcare. Yet current assumptions are based on general-purpose LLMs such as ChatGPT …

There is a growing interest in the area of machine learning and creativity. This survey
presents an overview of the history and the state of the art of computational creativity …

Story generation, namely, generating a reasonable story from a leading context, is an
important but challenging task. In spite of the success in modeling fluency and local …

We present a simple approach for text infilling, the task of predicting missing spans of text at
any position in a document. While infilling could enable rich functionality especially for …

Recent text generation research has increasingly focused on open-ended domains such as
story and poetry generation. Because models built for such tasks are difficult to evaluate …

Writers generally rely on plans or sketches to write long stories, but most current language
models generate word by word from left to right. We explore coarse-to-fine models for …

Generating a reasonable ending for a given story context, ie, story ending generation, is a
strong indication of story comprehension. This task requires not only to understand the …

Recent approaches to data-to-text generation have shown great promise thanks to the use
of large-scale datasets and the application of neural network architectures which are trained …

We present a memory-augmented approach to condition an autoregressive language model
on a knowledge graph. We represent the graph as a collection of relation triples and retrieve …