OMEGA: Optimizing Machine Learning by Evaluating Generated Algorithms
Jeremy Nixon, Annika Singh
cs.AI cs.LG
Abstract
In order to automate AI research we introduce a full, end-to-end framework, OMEGA: Optimizing Machine learning by Evaluating Generated Algorithms, that starts at idea generation and ends with executable code. Our system combines structured meta-prompt engineering with executable code generation to create new ML classifiers. The OMEGA framework has been utilized to generate several novel algorithms that outperform scikit-learn baselines across a robust selection of 20 benchmark datasets (infinity-bench). You can access models discussed in this paper and more in the python package: pip install omega-models.
Topics
Classified with taxonomy v2 on Wed, 2 Sept 2026.