This important study describes a deep learning framework that analyzes single-cell RNA data to identify a tumor-agnostic gene signature associated with brain metastases. The identified signature ...
Modern LLMs typically return answers through a token-by-token streaming process, where each token is packaged into a separate ...
The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior ...
Introduction: As the number of Internet of Things (IoT) devices grows quickly, cyber threats are becoming more complex and increasingly sophisticated; thus, we need a more robust network security ...
Abstract: This study provides a comparative evaluation of transformer models and Recurrent Neural Networks (RNNs) for text classification. As the complexity of the text data is growing and more ...
Abstract: In the context of accelerated digital transformation, cybersecurity has become a global strategic issue. With the rapid growth of network traffic and the evolving complexity of attack ...
Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...
Computer scientists have developed a new AI text-to-video model that learns real-world physics knowledge from time-lapse videos. While text-to-video artificial intelligence models like OpenAI's Sora ...
ABSTRACT: Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...
In recent decades, medical short texts, such as medical conversations and online medical inquiries, have garnered significant attention and research. The advances in the medical short text have ...
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