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 …

Transformer-based models have pushed state of the art in many areas of NLP, but our
understanding of what is behind their success is still limited. This paper is the first survey of …

In transfer learning, two major activities, ie, pretraining and fine‐tuning, are carried out to
perform downstream tasks. The advent of transformer architecture and bidirectional …

The emergence of pre-trained language models (PLMs) has shown great success in many
Natural Language Processing (NLP) tasks including text classification. Due to the minimal to …

Fake news permeating life through channels misleads people into disinformation. To reduce
the harm of fake news and provide multiple and effective news credibility channels, the …

Transformer-based models have been scaled up to account for absorbing more information
and improve their performances. However, several studies have called attention to their …

Transformer-based Large Language Models (LLMs) traditionally rely on final-layer loss for
training and final-layer representations for predictions, potentially overlooking the predictive …

In this paper, we introduce a new decoding method to mitigate the issue of hallucinations in
Large Language Models (LLMs). Specifically, our method dynamically selects appropriate …

Large pre-trained language models such as BERT have been the driving force behind
recent improvements across many NLP tasks. However, BERT is only trained to predict …

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 …