Text Generation aims to produce plausible and readable text in human language from input
data. The resurgence of deep learning has greatly advanced this field, in particular, with the …

Background: Few-shot learning (FSL) is a class of machine learning methods that require
small numbers of labeled instances for training. With many medical topics having limited …

In order to uncover the meanings of 'book of life', 155 different biological language models
(BLMs) for DNA, RNA and protein sequence analysis are discussed in this study, which are …

We study the pre-train+ fine-tune strategy for data-to-text tasks. Our experiments indicate that
text-to-text pre-training in the form of T5, enables simple, end-to-end transformer based …

We present DART, an open domain structured DAta Record to Text generation dataset with
over 82k instances (DARTs). Data-to-Text annotations can be a costly process, especially …

This survey provides a comprehensive review of research on multi-turn dialogue systems,
with a particular focus on multi-turn dialogue systems based on large language models …

Wind energy has emerged as a highly promising source of renewable energy in recent
times. However, wind turbines regularly suffer from operational inconsistencies, leading to …

In the last few years, the natural language processing community has witnessed advances
in neural representations of free texts with transformer-based language models (LMs). Given …

Data-to-text generation has recently attracted substantial interests due to its wide
applications. Existing methods have shown impressive performance on an array of tasks …

The ability to generalise well is one of the primary desiderata of natural language
processing (NLP). Yet, what'good generalisation'entails and how it should be evaluated is …