Equation 1 · Agent Evaluation in 2035: Two Axes, Four Scenarios, and What Would Falsify Them
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Whether automated LLM-judge evaluation becomes trusted for high-stakes decisions is not a third axis; it is mostly a readout of Axis A applied to one specific evaluator. A useful way to see the dependency is to write the automation decision as a threshold rule. Let be the estimated error rate of a judge on a decision class a , and let be the maximum error a policy is willing to tolerate for that stakes class. A defensible automation rule is
Sources cited in the article section
- [6] Frontier Capability Assessments ↗
- [1] Cheating Behaviour in Frontier Model Evaluations ↗
- [5] Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference ↗
- [11] Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena ↗
- [7] Anthropic's Responsible Scaling Policy ↗
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