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Study Formalizes "Efficiency Hallucination" in LLM Code Optimization
A new arXiv paper introduces the concept of "efficiency hallucination," describing how large language models sometimes propose code changes that do not alter functionality while claiming performance gains that are not actually supported. The authors formalize and measure this behavioral calibration problem to assess how reliably LLMs can justify their optimizations. The work aims to give researchers a way to quantify when model claims about speedups diverge from verified results.