Combining LLMs and Genetic Search for ARC-AGI-2
LLMs can generate programs for ARC-AGI-2 tasks, but the provided compute only allows a small number of attempts to generate, debug and validate solutions. Genetic algorithms can search and test many more programs, but random search rarely starts in a useful neighborhood of the solution space. We combine the two methods through a compact domain specific language (DSL). First, a quantized Qwen3.5-4B LLM generates an initial set of programs for each ARCAGI-2 task. Then, we use those programs to seed an initial population of starting programs, and use genetic algorithms to evolve these programs towards a solution to the given task. The DSL is designed such that every mutated program remains v...
| Authors | Val Dyachenko |
|---|---|
| Primary category | cs.NE |
| Published | 23 September 2026 |
| Last updated at source | 23 September 2026 |
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