AI Madness 2026 has been full of exciting twists and turns. As the ultimate proving ground for Large Language Models, each round showed that it is no longer enough for AI to simply be "correct," but ...
{"id": "math_001", "category": "math", "prompt": "Solve a simple example of Bayes theorem for spam filtering. Show your work.", "holdout": true} {"id": "math_002 ...
Agentic LLMs keep failing the same way because they lack specific, reusable capabilities. Stanford's TRACE diagnoses those gaps from an agent's own trajectories, synthesizes one verifiable training ...
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