The authorship verification task at PAN 2022 follows the experimental setup of similar
shared tasks in the recent past. However, it focuses on a different, and very challenging …

Accurate attribution of authorship is crucial for maintaining the integrity of digital content,
improving forensic investigations, and mitigating the risks of misinformation and plagiarism …

With the advent of the modern pre-trained Transformers, the text preprocessing has started
to be neglected and not specifically addressed in recent NLP literature. However, both from …

Large Language Models (LLMs) are advancing at a remarkable pace, with myriad
applications under development. Unlike most earlier machine learning models, they are no …

In this paper we describe a deep learning model based on a Data Augmentation (DA) layer
followed by a Convolutional Neural Network (CNN). The proposed model was developed by …

In this work we propose a novel ensemble model based on deep learning and non-deep
learning classifiers. The proposed model was developed by our team for participating at the …

This article is the third paper in a series aimed at the establishment of the authorship of
Russian-language texts. This paper considers methods for determining the authorship of …

The problem we address in this work is classifying whether a Twitter user has spread Irony
and Stereotype or not. We used a text vectorization layer to generate Bag-Of-Words …

This paper describes a proposed system design for Style Change Detection (SCD) tasks for
PAN at CLEF 2022. We propose a unified architecture of ensemble neural networks to solve …

Authorship verification is the task of determining whether or not the same author wrote two
texts based on comparing the texts. The PAN@ CLEF 2022 [1] Authorship Verification …