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arXiv · 2509.18108

Solve it with EASE

Adam Viktorin·Tomas Kadavy·Jozef Kovac·Michal Pluhacek·Roman Senkerik
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Abstract

This paper presents EASE (Effortless Algorithmic Solution Evolution), an open-source and fully modular framework for iterative algorithmic solution generation leveraging large language models (LLMs). EASE integrates generation, testing, analysis, and evaluation into a reproducible feedback loop, giving users full control over error handling, analysis, and quality assessment. Its architecture supports the orchestration of multiple LLMs in complementary roles-such as generator, analyst, and evaluator. By abstracting the complexity of prompt design and model management, EASE provides a transparent and extensible platform for researchers and practitioners to co-design algorithms and other generative solutions across diverse domains.

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Adam Viktorin, Tomas Kadavy, Jozef Kovac, Michal Pluhacek, Roman Senkerik. 2025-09-09. Solve it with EASE. https://arxiv.org/abs/2509.18108

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