Benchmark for statistically valid AI scientist systems, using audit-closed protocols, transparency logs, and sequential inference to prevent false discoveries in autonomous research agents.
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Updated
Aug 28, 2026 - Python
Benchmark for statistically valid AI scientist systems, using audit-closed protocols, transparency logs, and sequential inference to prevent false discoveries in autonomous research agents.
Find feature-specific failures in quantile forecasts as outcomes arrive.
Certified branch/tool gating evidence harness for public agent workloads
CertiScale 衡证 · 可证明的推理时计算规模化:CITE × 验证器校准 e-process × 共享预算分配。Anytime-valid Type-I 错误可证,FDR 较 CITE 降 21-43×。作者:晨星
Official code and reproducibility materials for e-ATS: e-process-authorized Thompson sampling for non-stationary bandits. NeurIPS 2026 E-Values Workshop.
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