AI RESEARCH
Structured Prompts Improve Evaluation of Language Models
arXiv CS.AI
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ArXi:2511.20836v3 Announce Type: replace-cross As language models (LMs) are increasingly adopted across domains, high-quality benchmarking frameworks are essential for guiding deployment decisions. In practice, however, frameworks such as Holistic Evaluation of Language Models (HELM) typically evaluate models under a single static prompt configuration, even though model behavior depends strongly on prompt choice. As a result, reported scores can reflect prompt choice as much as model capability.