Pre-trained language models have achieved striking success in natural language
processing (NLP), leading to a paradigm shift from supervised learning to pre-training …

Data augmentation, the artificial creation of training data for machine learning by
transformations, is a widely studied research field across machine learning disciplines …

Generative Large Language Models (LLMs) such as GPT-3 are capable of generating highly
fluent responses to a wide variety of user prompts. However, LLMs are known to hallucinate …

Considerable progress has recently been made in natural language processing: deep
learning algorithms are increasingly able to generate, summarize, translate and classify …

Large language models (LLMs) have demonstrated impressive capabilities in natural
language processing. However, their internal mechanisms are still unclear and this lack of …

Abstract Vision-and-language (VL) pre-training has proven to be highly effective on various
VL downstream tasks. While recent work has shown that fully transformer-based VL models …

Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …

Recently, prompt tuning has been widely applied to stimulate the rich knowledge in pre-
trained language models (PLMs) to serve NLP tasks. Although prompt tuning has achieved …

A fundamental characteristic common to both human vision and natural language is their
compositional nature. Yet, despite the performance gains contributed by large vision and …

Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved
great success and become a milestone in the field of artificial intelligence (AI). Owing to …