SOURCE-LINKED INTELLIGENCE
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 to
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-23T02:25:38.000Z
First collected: 2026-09-24T01:22:21.678Z. This is not the publication date.