The Generative Pre-trained Transformer (GPT) represents a notable breakthrough in the
domain of natural language processing, which is propelling us toward the development of …

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

This study aims to develop a system for automatically correcting spelling errors in Persian
texts using two approaches: one that relies on rules and a common spelling mistake list and …

Etching technology–one of the representative modern semiconductor device makers–serves
as a broad descriptor for the process of removing material from the surfaces of various …

Organic solar cells (OSCs) are a promising photovoltaic technology for practical
applications. However, the design and synthesis of donor materials molecules based on …

The number of Language Models (LMs) dedicated to processing scientific text is on the rise.
Keeping pace with the rapid growth of scientific LMs (SciLMs) has become a daunting task …

Objectives: This survey aims to provide an overview of the current state of biomedical and
clinical Natural Language Processing (NLP) research and practice in Languages other than …

The rapid progress in deep learning has propelled transformer-based models to the
forefront, establishing them as leading solutions for a multiple NLP tasks. These tasks span …

Text classification aims to assign predefined labels to unlabeled sentences, which tend to
struggle in real-world applications when only a few annotated samples are available …

Metallic cathodes are one of reasons for instability in perovskite solar cells due to reaction
with halogens I−, Br−, and it is desirable to have stable carbon‐based cathodes, particularly …