AI Research & MathematicsIntermediate4.5 hours
Evaluating Reasoning Models: Benchmarks, Verifiers, and Alignment
Rigorous methodologies for evaluating chain-of-thought models, mathematical verifiers, and safety red-teaming.
Course Overview & Objectives
Learn how frontier labs design benchmark suites that resist data contamination. Explore automated verifiers, RLVR (reinforcement learning with verifiable rewards), and safety evaluations.
Zoya Farooq
Senior Research & AI Models EditorSpecializes in reviewing pre-print publications, benchmark reliability, mechanistic interpretability, and post-training reinforcement learning.
Enrollment & Access Status
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Curriculum Syllabus
1 Modules • 1 Lessons1
1 lessonsModule 1: Foundations of Benchmark Contamination
Evaluating modern benchmarks, test set leakage, and synthetic verification pipelines.