AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systems

The evolution towards 6G architecture promises a transformative shift in communication networks, with artificial intelligence (AI) playing a pivotal role. This paper delves deep into the seamless integration of Large Language Models (LLMs) and Generalized Pretrained Transformers (GPT) within 6G systems. Their ability to grasp intent, strategize, and execute intricate commands will be pivotal in redefining network functionalities and interactions. Central to this is the AI Interconnect framework, intricately woven to facilitate AI-centric operations within the network. Building on the continuously evolving current state-of-the-art, we present a new architectural perspective for the upcoming generation of mobile networks. Here, LLMs and GPTs will collaboratively take center stage alongside traditional pre-generative AI and machine learning (ML) algorithms. This union promises a novel confluence of the old and new, melding tried-and-tested methods with transformative AI technologies. Along with providing a conceptual overview of this evolution, we delve into the nuances of practical applications arising from such an integration. Through this paper, we envisage a symbiotic integration where AI becomes the cornerstone of the next-generation communication paradigm, offering insights into the structural and functional facets of an AI-native 6G network

Page Segmentation and Classification Using Fast Feature Extraction and Connectivity Analysis

Page segmentation and classification are important parts of the document analysis process. The aim is to extract and classify different parts of the page. This paper proposes an approach in which these two phases are combined. The integration process includes fast feature extraction with rule-based classification and label propagation using connectivity analysis providing classified areas in three categories: background, text and picture. Keywords: segmentation, classification, fast feature extraction, rule-based reasoning, connectivity analysis. 1. Introduction There is an ever growing demand for electronic and computerized document management, storage and circulation. This has been a problem for governments and corporations in the past, but nowadays also considerable consuming masses, ordinary people, have grown to demand these basic tasks. Document structure analysis and understanding are the main processes in reaching this goal: ease of use and availability of documents. The lates..