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 …

Deep Neural Networks (DNNs) are nowadays a common practice in most of the Artificial
Intelligence (AI) applications. Their ability to go beyond human precision has made these …

In recent years, generative transformers have become increasingly prevalent in the field of
artificial intelligence, especially within the scope of natural language processing. This paper …

In this paper, we present a comprehensive mathematical analysis of the hallucination
phenomenon in generative pretrained transformer (GPT) models. We rigorously define and …

With the recent advances in deep learning, different approaches to improving pre-trained
language models (PLMs) have been proposed. PLMs have advanced state-of-the-art …

Transformer architectures are highly expressive because they use self-attention
mechanisms to encode long-range dependencies in the input sequences. In this paper, we …

Social media has become an essential facet of modern society, wherein people share their
opinions on a wide variety of topics. Social media is quickly becoming indispensable for a …

Due to the proliferation of large language models (LLMs) and their widespread use in
applications such as ChatGPT, there has been a significant increase in interest in AI over the …

The body of scientific literature continues to grow annually. Over 1.5 million abstracts of
biomedical publications were added to the PubMed database in 2021. Therefore …

One of the major obstacles in reaching diagnostic consensus is observer variability. With the
recent success of artificial intelligence, particularly the deep networks, the question emerges …