Verified70% confidenceFactExact time
RLHF was formally systematized by the InstructGPT paper in 2022, with a basic three-step process: collecting human preference data to train a reward model, optimizing the language model using reinforcement learning algorithms such as PPO, and continuous iteration.
4
Sources
70%
Confidence
Long-term
Relevance
7/25/2026
First Seen
Sources
OpenAI Releases GPT-5.6 and ChatGPT Work: The Era of Autonomous AI Has Arrived
bilibili皮皮蟹勇闯天涯7/11/2026
Related Claims
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.84% similarVerifiedInstruction fine-tuning was systematically proposed by InstructGPT (2022), combining reinforcement learning from human feedback (RLHF) to make models better aligned with human intent.82% similarVerifiedModern large language models typically go through three training stages: pre-training, supervised fine-tuning (SFT), and reinforcement learning from human feedback (RLHF).77% 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77% similar
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