Unverified50% confidenceOpinionExact time
Both the PPO and RLCD approaches attempt to move away from the autoregressive paradigm and use reinforcement learning to produce structured probabilistic or confidence outputs.
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9/17/2026
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UnverifiedRLHF遵循先用监督微调（本质是行为克隆）建立基础能力，再用PPO等算法优化人类偏好目标的范式75% similarUnverifiedThe controllability of generative systems is typically mitigated through two types of mechanisms: reinforcement learning alignment (RLHF/RLAIF) and deterministic constraint layers.75% similarUnverifiedPPO in RLHF scenarios requires simultaneously maintaining four neural networks: the policy model, reference model, reward model, and value model.75% similarUnverifiedDirect Preference Optimization（DPO，2023年）通过数学变换将RLHF的两阶段问题压缩为单阶段监督学习，无需显式奖励模型74% similar
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