By treating web search and problem-solving as co-evolving processes rather than separate steps, EvoDuet helps LLMs avoid getting stuck when they need external knowledge, improving discovery performance by 4-21% across scientific optimization tasks.
EvoDuet is a method that improves how AI models search the web while solving scientific problems. It co-evolves search queries and solutions together, letting the model decide when to search for new information versus reusing old documents. The system uses an inner loop to refine searches and an outer loop to generate solutions, achieving significant improvements on optimization tasks.