Systems and methods for scalable guard rails for LLMs in code generation
Abstract
The invention relates to a method of using language models, e.g. large language models (LLM), for scalable and error-free code generation for create, read, update, and delete (CRUD) applications with role-based access control.
Fields of Study & Subjects
Software Engineering Research
Access Control and Trust
Adversarial Robustness in Machine Learning
Publication details
- Journal / source
- Figshare
- Publication date
- 1 January 2026