EvoLattice: Evolving LLM-Guided Program Discovery with Quality-Diversity Graphs
Published:Dec 15, 2025 19:43
•1 min read
•ArXiv
Analysis
This research introduces EvoLattice, a novel approach to program discovery using Large Language Models (LLMs) and quality-diversity graph representations. The work potentially addresses the challenge of exploring complex program spaces by maintaining a diverse population.
Key Takeaways
- •EvoLattice employs quality-diversity graph representations for program discovery, enhancing exploration of the solution space.
- •The approach leverages LLMs to guide the program discovery process, potentially improving efficiency and effectiveness.
- •The research focuses on persistent internal-population evolution through graph-based representations.
Reference
“EvoLattice utilizes multi-alternative quality-diversity graph representations for LLM-guided program discovery.”