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.
Original Excerpt
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 »