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Reinforcement learning towards broadly and persistently beneficial models

alignment.openai.com · 2,332 words · saved by 6 readers

Training targeting beneficial behavior in realistic scenarios produces broad improvements in alignment that generalize across domains and persist under adversarial pressure.

Reinforcement learning towards broadly and persistently beneficial models ← Back to OpenAI Alignment Blog Reinforcement learning towards broadly and persistently beneficial models Jun 18, 2026 · Akshay V. Jagadeesh, Rahul K. Arora, Khaled Saab, Ali Malik, Mikhail Trofimov, Foivos Tsimpourlas, Johannes Heidecke, Karan Singhal Correspondence: ajag@openai.com , karan@openai.com Read the paper TL;DR We find that reinforcement learning on realistic scenarios targeting beneficial traits can produce broad improvements across dozens of benchmarks measuring aligned and beneficial behavior.

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