Publicatii recente
Publicatii recente
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LLM Output Compliance with Handcrafted Linguistic Features: An Experiment (2025)
Abstract Can we control the writing style of large language models (LLMs) by specifying desired linguistic features? We address this question by investigating the impact of handcrafted linguistic feature (HLF) […]
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Alexa and Copilot: A Tale of Two Assistants (2025)
Abstract As virtual assistants (VAs) become essential to contemporary interactions, it is imperative to understand how to evaluate their functionalities. This study offers a comparison framework for assessing the design […]
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The Impact of Augmentation Techniques on Icon Detection Using Machine Learning Techniques (2024)
Abstract This article examines the use of image augmentation techniques to improve icon detection in mobile interfaces, a critical task due to the small size of graphical user interface (GUI) […]
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PyResolveMetrics: A Standards-Compliant and Efficient Approach to Entity Resolution Metrics (2024)
Abstract Entity resolution, the process of discerning whether multiple data refer to the same real-world entity, is crucial across various domains, including education. Its quality assessment is vital due to […]
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Malicious Web Links Detection Based on Image Processing and Deep Learning Models (2024)
Abstract The latest improvements regarding the online world have come with great benefits, but, as well as dangerous drawbacks (i.e., web-malware). This article proposes to investigate the reliability and accuracy […]
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Automatic Classification of Signal and Noise in Functional Magnetic Resonance Imaging Scans Using Convolutional Neural Networks (2024)
Abstract The integration of Artificial Intelligence (AI), particularly deep learning models like VGG16 and ResNet50, in the analysis of functional magnetic resonance imaging (fMRI) data has significantly advanced our understanding […]
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A Pseudo-Deterministic Noisy Extremal Optimization algorithm for the pairwise connectivity Critical Node Detection Problem (2024)
Abstract The critical node detection problem is a central task in computational graph theory due to its large applicability, consisting in deleting $k$ nodes to minimize a certain graph measure. […]
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Competitive Influence Maximization in Trust-Based Social Networks With Deep Q-Learning (2024)
Abstract Social network analysis is a rapidly evolving research area having several real-life application areas, e.g. digital marketing, epidemiology, spread of misinformation. Influence maximization aims to select a subset of […]
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Machine-Learning-Based Approaches for Multi-Level Sentiment Analysis of Romanian Reviews (2024)
Abstract Sentiment analysis has increasingly gained significance in commercial settings, driven by the rising impact of reviews on purchase decision-making in recent years. This research conducts a thorough examination of […]
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ContRail: A Framework for Realistic Railway Image Synthesis using ControlNet (2024)
Abstract Our research focuses on creating a framework for extracting 3D deformable objects from 2D scenes. We research the possibility of using multiple graph convolutional operators and depth estimators to […]
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