Advance techniques across the post-training stack: SFT, RLHF, RLAIF, DPO, preference learning, and reward modeling to align models with human intent and aesthetic judgment * Deep experience across the post-training stack, not just one slice: reward modeling, preference learning, RLHF/RLAIF, and personalization
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