Fortuna: Weighting Graders 75% Accuracy and 25% Style Mitigates Reward Hacking
Brendan Fortuna · ⚡️Using RFT to Build Clinical Superintelligence · Jul 29, 2025 · at 10:28
Brendan Fortuna, Head of Engineering at Ambience AI, explains how weighting both semantic accuracy and tone/style eliminated model reward hacking during clinical note generation.
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“So what we did is in the grader, you know, in addition to just the content and like the semantic accuracy of what it's saying, we also started to add style. And we kind of weight them like 75, 25, and over time you can kind of harness and get the reward hacking to go away.”
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