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ML Research Desk
Updated 2026-08-19
Technical evaluations of machine-learning methods, benchmark contamination dynamics, synthetic data distillation, and reasoning model architectures.
Benchmark Design
Synthetic Data Contamination and Benchmark Integrity in Frontier Reasoning Models: Measurement, Decontamination, and Failure Modes
An investigation into benchmark leakage, synthetic data contamination, and detection methodologies across frontier mathematical and code reasoning evaluations.