Most languages use word position and sentence structure to extract meaning. For example, "The cat sat on the box," is not the ...

ABSTRACT: The transitional blending between terrain and objects is a core challenge in enhancing the realism of game scenes. Aiming at the problems of poor universality, reliance on high-configuration ...

The field of quantum machine learning, which aims to leverage quantum computing to improve upon classical machine learning, has made notable progress recently. A study published in Intelligent ...

In QML, classical data must be encoded into quantum states. This process maps classical data to a quantum Hilbert space, allowing quantum operations to be performed on it. Various encoding techniques ...

Abstract: The new coding standard Versatile Video Coding (VVC) introduces additional encoding techniques based on the existing video coding standard, such as the difference in block partition ...

Abstract: The existing body of research on quantum embedding techniques is not only confined in scope but also lacks a comprehensive understanding of the intricacies of the quantum embedding process.

This study explores the integration of quantum data embedding techniques into classical machine learning (ML) algorithms; to assess performance enhancements and computational implications across a ...

Large language model (LLM) research and applications have advanced remarkably in recent years. These generative models have enthralled the artificial intelligence community, and many models trained on ...

encodify is a powerful Python module designed to provide a suite of advanced encoding techniques for Python scripts. These encoding methods encompass compression, base64 encoding, and XOR encryption, ...

Transformer-based Language Models have uplifted the domain of Natural Language Processing (NLP) in recent years. Their capacity to comprehend and produce text that is human-like has resulted in ground ...