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Results for “competition”
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The Predictive AI Evaluation Competition is open
The competition accepts code submissions through 20 November 2026 at 23:59 AoE.
The Predictive AI Evaluation Competition at NeurIPS 2026
Predict whether an AI system answered a benchmark question correctly. Submissions are Python code, evaluated with Brier scores reported for each AI subject and benchmark combination.
AIMS Resources
The textbook, the course, the competition, the tools, and the community channels. Pick a starting point.
Call for papers: AI Measurement Science Workshop at COLM 2026
AIMS is organizing a one-day workshop on rigorous AI measurement, co-located with COLM 2026 in San Francisco. The research and competition tracks are now open.
The AIMS community hub is live
AIMS now has a public home for the textbook, course, data and software, competition, blog, and community.
About AIMS
Why measuring AI requires strong scientific foundations, and what AIMS at Stanford is building to support them.
AI Measurement Science Workshop
A one-day workshop on the science of measuring frontier AI systems: measurement under interaction, strategic optimization, and non-stationarity.
CS 321M: AI Measurement Science at Stanford
Frameworks and methodologies for measuring, benchmarking, and understanding AI systems.
AIMS — AI Measurement Science
Stanford AIMS brings together research, teaching, and open resources for AI Measurement Science: the study of how AI systems are measured and understood.
Predicting AI Benchmark Performance with Lookup Tables, Item Text Features, and Lightweight Calibration
Annika Kaul Singh — The assignment I had was to build a predictor for whether an AI model would correctly answer a hidden benchmark item. The main challenge is that the test items are new, while the test subjects are models…