Publicatii recente
Publicatii recente
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Evaluating Deep Learning Models for Cross-Platform UI Component Detection: A Study Across Web, Desktop, and Mobile Interfaces (2025)
Abstract User interfaces look different across web, desktop, and mobile platforms — not just in layout, but in how buttons, icons, and text appear. This makes it hard for deep […]
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Synthetic Data Generation Using Large Language Models: Advances in Text and Code (2025)
Abstract This survey reviews how large language models (LLMs) are transforming synthetic training data generation in both natural language and code domains. By producing artificial but task-relevant examples, these models […]
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Unveiling Hybrid Cyclomatic Complexity: A Comprehensive Analysis and Evaluation as an Integral Feature in Automatic Defect Prediction Models (2025)
Abstract The complex software systems developed nowadays require assessing their quality and proneness to errors. Reducing code complexity is a never-ending problem, especially in today's fast pace of software systems […]
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TF1-EN-3M: Three Million Synthetic Moral Fables for Training Small, Open Language Models (2025)
Abstract Moral stories are a time-tested vehicle for transmitting values, yet modern NLP lacks a large, structured corpus that couples coherent narratives with explicit ethical lessons. We close this gap […]
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Small Open Models Achieve Near Parity with Large Models in Low Resource Literary Translation at a Fraction of the Cost (2025)
Abstract Literary translation has recently gained attention as a distinct and complex task in machine translation research. However, the translation by small open models remains an open problem. We contribute […]
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Textural analysis and artificial intelligence as decision support tools in the diagnosis of multiple sclerosis – a systematic review (2025)
Abstract Introduction Magnetic resonance imaging (MRI) is conventionally used for the detection and diagnosis of multiple sclerosis (MS), often complemented by lumbar puncture—a highly invasive method—to validate the diagnosis. Additionally, […]
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Hybrid Adaptive Greedy Algorithm Addressing the Multi-Robot Path Planning Problem (2025)
Abstract In the past few years, path planning and scheduling became a high-impact research topic due to their real-world applications such as transportation, manufacturing and robotics. This paper focuses on […]
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UOLO: A Multitask U-Net YOLO Hybrid Model for Railway Scene Understanding (2025)
Abstract Extracting essential information including the topological structure of rail-tracks, the position of switches and their current state can increase safety by reducing human error, while also boosting the efficiency […]
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A Hybrid Granular Ball-Ant Colony Optimization for the Multi-Depot Half-Open Time-Dependent Electric Vehicle Routing Problem (2025)
Abstract Electric vehicles (EVs) are increasingly utilized in logistics and distribution to expedite achieving carbon peaking and neutrality goals, drawing considerable attention to the Electric Vehicle Routing Problem (EVRP). This […]
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ContRail: Realistic Railway Image Synthesis using ControlNet (2025)
Abstract Deep learning became an ubiquitous paradigm due to its extraordinary effectiveness and applicability in numerous domains. However, the approach suffers from the high demand for data required to achieve […]
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