ExPairT-LLM: Exact Learning for LLM Code Selection by Pairwise Queries

ExPairT-LLM is introduced as an exact learning algorithm aimed at improving code selection from multiple outputs generated by large language models (LLMs). Traditional code selection algorithms often struggle to identify the correct program due to misidentification of nonequivalent programs or reliance on LLMs that may not always provide accurate outputs. ExPairT-LLM addresses these issues by utilizing pairwise membership and pairwise equivalence queries, enhancing the accuracy of program selection. Evaluations show a significant improvement in success rates over existing algorithms.