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The Direct Preference Optimization Family

Rafailov et al. (2023) showed RLHF's optimum has a closed form in terms of the preference data, so you can skip the explicit reward model and optimize the policy directly. That insight spawned a family - IPO, KTO, SimPO, ORPO, BPO - each…

LearnPython (stdlib, six-variant preference-loss comparator) 1.5 h Paid plans
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