Latest Articles for Computer Science

Simulation tools are essential for developing and testing quantum networking technologies.

Discover how triorthogonal codes enhance quantum error correction techniques.

Examining stability issues in polynomial rootfinding techniques.

A look into conditional independence and its role in statistical modeling.

A new method enhances theorem proving using AI and expert learning.

IST-SAT promises faster solutions for complex optimization problems using quantum mechanics.

This study presents a new method to enhance QAOA efficiency and accuracy.

GraphFSA enhances machine learning by applying finite state automata to graph structures.

New strategies enhance color assignment in virtual graphs despite communication constraints.

Research enhances understanding of random Turan numbers and hypergraph structures.

Explore how randomization enhances algorithm design and performance.

Discover how GRC enhances communication in distributed computing systems.

A new method improves verification of safety properties in finite instances.

Research sheds light on grokking behavior in machine learning models tackling modular arithmetic.

This article examines a method for assessing LLM-generated code accuracy.

A framework combining AFT and Category Theory for higher-order logic applications.

Examining the ties and solutions between Max-Cut and Maximum Independent Set.

Integrating large language models improves the clarity of automated unit tests.

Discovering methods to optimize binary matroids through effective algorithm design.

A new approach to enhance decision tree models in reinforcement learning.

New quantum algorithms improve optimization problem solutions, particularly Max-SAT.

Explore how verification and synthesis improve software reliability in complex systems.

New methods improve the calculation of elliptic functions with high precision.

This article discusses a method to manipulate neural networks without triggers.

A look at Binary Search Trees and Huffman trees under uncertainty.

This article explores the behavior of graphs during edge retention randomness.

Propper enhances ILP systems to learn effectively from uncertain data.

This article presents an algorithm for creating consensus clusterings from various graph partitions.

This article covers a system that manages communication between processes using sandboxes.

A look into how numbers can be partitioned and their significance.

Examining graph coloring methods and their implications on structure and applications.

A look at using barrier certificates for safer quantum circuit verification.

A look into efficient AI using SNNs and IMC technology.

The SEBQ scheme offers advanced security in symmetric encryption using quasigroups.

A new method merges AI techniques for improved learning from data.

Researchers present a faster way to solve complex differential equations using random walks.

Learn how model pruning enhances AI performance and reduces resource needs.

Learn how to craft specifications for programs with complex behaviors.

Discover how deep learning mimics brain function to enhance machine learning.

A new approach to assess language models with varied instructions and tasks.