I audited 112 real RL post-training environments for reward-hacking vulnerabilities — 54 flagged, 0 false positives [OC, tool] [P]
This story is from 2026-09-01. It is preserved in the archive; the latest stories are on the live feed.
RL post-training (RLHF/RLAIF/GRPO) agents optimize strictly for whatever the verifier rewards. If the verifier has logic flaws, the agent learns to hack the grader instead of solving the task — recent work has catalogued this at scale (Terminal Wrench found 331 hackable environments and 15%+ of sta…
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Timeline · 2 reports
- 2026-09-01 16:35 · r/reinforcementlearning
I audited 112 real RL post-training environments for reward-hacking vulnerabilities — 54 flagged, 0 false positives [OC, tool] [P] - 2026-09-01 16:34 · r/MachineLearning
I audited 112 real RL post-training environments for reward-hacking vulnerabilities — 54 flagged, 0 false positives [OC, tool] [P]