nicola-ibrahim/aad_llm

aad-llm is a notebook-first research framework that evolves Python black-box optimizers with an LLM, evaluates candidates on noisy BBOB problems, and independently benchmarks selected champions against classical methods. The map follows the documented experiment workflow and preserves separate audit, statistical-analysis, and optional generalization branches. Paths come from the supplied tree; several application and analysis internals were not sampled, so their uncertain call wiring is intentionally omitted.