In this article, we provide a comprehensive introduction to knowledge graphs, which have
recently garnered significant attention from both industry and academia in scenarios that …

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 …

Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …

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 …

This paper explores a simple method for improving the zero-shot learning abilities of
language models. We show that instruction tuning--finetuning language models on a …

The dominant paradigm of natural language processing consists of large-scale pre-training
on general domain data and adaptation to particular tasks or domains. As we pre-train larger …

With the ever-growing size of pretrained models (PMs), fine-tuning them has become more
expensive and resource-hungry. As a remedy, low-rank adapters (LoRA) keep the main …

Data augmentation has recently seen increased interest in NLP due to more work in low-
resource domains, new tasks, and the popularity of large-scale neural networks that require …

Fine-tuning is the de facto way to leverage large pretrained language models to perform
downstream tasks. However, it modifies all the language model parameters and therefore …

Prompt-learning has become a new paradigm in modern natural language processing,
which directly adapts pre-trained language models (PLMs) to $ cloze $-style prediction …