AI RESEARCH
QuickScope: Certifying Hard Questions in Dynamic LLM Benchmarks
arXiv CS.CL
•
ArXi:2604.17842v1 Announce Type: new LLM benchmarks are increasingly dynamic: instead of containing a fixed set of questions, they define templates and parameters that can generate an effectively unlimited number of question variants. This flexibility is valuable, but it makes evaluation expensive -- especially when the goal is not just determining an average score, but reliably identifying a model's weak spots. This paper