Show HN: Rare Failure Eval
Category: ai-ml
Tags: evaluation, agent-benchmark, rare-failures, sampling, reproducible-research
Score: 5.8/10 (Innovation: 6, Technical: 5, Documentation: 8, Utility: 4)
Rare Failure Eval is a reproducible Python experiment that compares sampling policies for evaluating AI agents under fixed budgets, focusing on rare failures where selection accuracy and expected utility loss can diverge. It provides a synthetic benchmark with simulated worlds, detailed reports, and an independent audit, offering a nuanced perspective on evaluation metrics.
Target audience: AI researchers, ML engineers, evaluation framework developers
Repository: https://github.com/itsloganmann/rare-failure-eval · Python · 1 stars
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