Verified90% confidenceFactTime unknown
Modern large language models typically go through three training stages: pre-training, supervised fine-tuning (SFT), and reinforcement learning from human feedback (RLHF).
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6/1/2026
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VerifiedThe RLHF pipeline consists of three steps: training a reward model to predict human preference scores, adjusting language model parameters using the PPO reinforcement learning algorithm, and using KL divergence constraints to prevent the model from deviating from its original language capabilities.78% similarVerifiedRLHF（基于人类反馈的强化学习）是ChatGPT等对话模型背后的关键训练技术78% similarVerified大语言模型在RLHF训练阶段，因人类标注员倾向于给更详细、更礼貌的回答打高分，导致模型学会了过度冗长的表达模式77% similarUnverifiedIn ChatGPT's training, the pre-training phase uses unsupervised learning for next-token prediction, the instruction fine-tuning phase introduces supervised learning, and finally RLHF is used to align the model's outputs.77% similar
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