IEEE

Model-Agnostic Empirical Evaluation of Test-Driven Prompt Engineering on Improving Accuracy and Efficiency in Large Language Models Python Code Generation

Abstract: Although Large Language Models (LLMs) are widely adopted for code generation, the generated code can be semantically incorrect, requiring iterations of evaluation and refinement. Test-driven ...
GitHub

Stroke capacity planning model: python DES RAP

This repository is an example accompanying the DES RAP Book — an open educational resource on reproducible discrete-event simulation (DES) in Python and R. The book demonstrates best practices for ...
GitHub

bethington/cheat-engine-server-python

This server operates in READ-ONLY mode for safety. It can read and analyze memory but cannot modify it. All operations are logged for security auditing.
IEEE

Asymmetric t-GARCH(1,1) Model for Heuristic Kalman Filtering

Abstract: In this letter, the novel asymmetric t-GARCH(1,1) (ATGARCH(1,1)) model is proposed. By calculating the tail exponent (TE), it is discovered that the TE of the ATGARCH(1,1) distribution is ...