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AI4AI-Bench Tasks Agents With Rewriting Ten Types of Training Algorithms; Best System Averages Just 0.250
AI4AI-Bench evaluates hyperparameter tuning separately from genuine changes to learning methods, requiring coding agents to submit training code that can be rerun from scratch. Across 290 trials involving six systems, more than 40% underperformed the original algorithms, while increased reasoning effort mainly made agents more willing to modify core training mechanisms.