How Researchers Test AI Agents: A Review of LLM Evaluation Methods

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Overview

• Survey examining how LLM-based agents are evaluated
• Covers assessment frameworks for agent capabilities, behaviors, and performance
• Identifies gaps in evaluation methodologies
• Proposes a more standardized approach to agent evaluation
• Emphasizes the importance of reproducible benchmarks for agent development

Plain English Explanation

When we build AI agents powered by large language models (LLMs), we need ways to test how well they work. This paper surveys the different methods researchers use to evaluate these [LLM-based agents](https://aimodels.fyi/papers/arxiv/survey-large-language-model-based-autonomous...

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