Small LLM Eval Sets Beat Fake Big Ones
中文摘要
针对特定失败类别设计的精简评估集，其效果优于大规模随机数据集。
English Summary
Carefully designed small evaluation sets outperform large, random datasets by targeting specific failure categories in LLMs.
原文节选
Why a small, designed eval set with real failure categories can be more useful than a large random folder of examples. Continue reading on Medium »