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

Large text documents are sometimes challenging to understand and time-consuming to
extract vital information from. These issues are addressed by automatic text summarizing …

Conversational systems are now applicable to almost every business domain. Evaluation is
an important step in the creation of dialog systems so that they may be readily tested and …

This study aims to provide insights into the COVID-19-related communication on Twitter in
the Republic of Croatia. For that purpose, we developed an NL-based framework that …

The effectiveness of existing AI detectors is notably hampered when processing Arabic texts.
This study introduces a novel AI text classifier designed specifically for Arabic, tackling the …

The Internet of Things is a paradigm that interconnects several smart devices through the
internet to provide ubiquitous services to users. This paradigm and Web 2.0 platforms …

Current AI detection systems often struggle to distinguish between Arabic human-written text
(HWT) and AI-generated text (AIGT) due to the small marks present above and below the …

This work uses sequence-to-sequence (seq2seq) models pre-trained on monolingual
corpora for machine translation. We pre-train two seq2seq models with monolingual corpora …

Achieving carbon neutrality by 2050 requires unprecedented technological, economic, and
sociological changes. With time as a scarce resource, it is crucial to base decisions on …

This article studies a composer style classification task based on raw sheet music images.
While previous works on composer recognition have relied exclusively on supervised …