Revolutionizing LLM/Agent Evaluation: The Power of Flexible Tagging

This article introduces a brilliant new approach to evaluating Large Language Models (LLMs) and Agents. Instead of rigid categories, the author champions the use of multiple tags, allowing for dynamic analysis and effortless data exploration. This innovative method promises to streamline LLM evaluation and unlock deeper insights.

• •The article proposes using multiple tags (labels) instead of rigid categories for LLM/Agent evaluation data.
• •This approach enables flexible analysis and allows for adding new analysis axes by simply adding more tags.
• •The data structure remains unchanged, making it easy to adapt and expand the evaluation process.