Benchmarking for AI agents favors models that perform well on tests but fail in real-world use, requiring evaluation reforms emphasizing realistic tasks, goals, and environments.
How Reliable Are Human Judgments in AI Model Testing? | HackerNoon
Human evaluations showed high agreement among annotators, indicating reliability in assessing model performance, particularly on objective content evaluations.