Preprint Open access
Are you Synthesizing or Recalling? Evaluating LLMs on Algorithmic Code Retrieval
Large language models (LLMs) have demonstrated strong performance in code generation, where success depends on both recalling relevant algorithmic knowledge and reasoning about how to apply it. However, existing LLM pipelines are opaque, with no explicit separation between these two components. We argue that for well-k …