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Brian Lee

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Post-Training at the Edge of Detectability: A Game-Theoretic Approach to Fine-Tuning

This work proposes a game-theoretic framework that gives this reward-retention trade-off an explicit statistical interpretation, and provides a principled method for learning this equilibrium coefficient via reduction to the KL-regularized RL objective, thus allowing for flexible integration into standard fine-tuning p...

Keegan Harris, Brian Lee, Ian Waudby-Smith et al. · 0 citations

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