AI RESEARCH
EffiPair: Improving the Efficiency of LLM-generated Code with Relative Contrastive Feedback
arXiv CS.AI
•
ArXi:2604.05137v1 Announce Type: cross Large language models (LLMs) often generate code that is functionally correct but inefficient in runtime and memory. Prior approaches to improving code efficiency typically rely on absolute execution feedback, such as profiling a single program's runtime or memory usage, which is costly and provides weak guidance for refinement. We propose Relative Contrastive Feedback (RCF), an inference-time feedback mechanism that requires no model fine-tuning or parameter updates.