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- Meta Releases HackBench for Detecting Reward Hacking in Research Agents
Meta AI’s RAM research team released HackBench, a benchmark for detecting and locating reward hacking in autonomous research agents, according to DoNews. Its 169 audited trajectories include 41 native cases and 128 synthetic samples, with command-level labels for evaluating precision, recall and F1; Claude Opus 5 led the reported models with an F1 score of 64.88. Meta has published the trajectories and labels, while the full technical report is planned for arXiv.
DoNews · 🔥 0
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