TextBFGS: A Case-Based Reasoning Approach to Code Optimization via Error-Operator Retrieval

ArXi:2602.00059v2 Announce Type: replace-cross Iterative code generation with Large Language Models (LLMs) can be viewed as an optimization process guided by textual feedback. However, existing LLM self-correction methods predominantly operate in a stateless, trial-and-error manner akin to first-order search, failing to leverage past problem-solving experiences. To bridge this gap, we