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Dictionary

RLHF

Reinforcement learning from human feedback, the alignment technique behind ChatGPT.

1 min readupdated 2026-07-04

/ quick answer

RLHF trains a reward model from human preference pairs, then fine-tunes the base LLM with PPO to maximize that reward. Result: models that follow instructions and refuse unsafe requests. Reinforcement learning from human feedback, the alignment technique behind ChatGPT.

Reinforcement learning from human feedback, the alignment technique behind ChatGPT. RLHF trains a reward model from human preference pairs, then fine-tunes the base LLM with PPO to maximize that reward. Result: models that follow instructions and refuse unsafe requests. In practice: ChatGPT's instruction-following polish comes from RLHF applied on top of GPT-3.5. This dictionary node is part of the Onexial knowledge graph and links to related concepts, workflows and tools below.
Definition
RLHF trains a reward model from human preference pairs, then fine-tunes the base LLM with PPO to maximize that reward. Result: models that follow instructions and refuse unsafe requests.
Example
ChatGPT's instruction-following polish comes from RLHF applied on top of GPT-3.5.
/ frequently asked

What is RLHF?

RLHF trains a reward model from human preference pairs, then fine-tunes the base LLM with PPO to maximize that reward. Result: models that follow instructions and refuse unsafe requests.

What is an example of RLHF?

ChatGPT's instruction-following polish comes from RLHF applied on top of GPT-3.5.

Why does RLHF matter for AI and automation?

Reinforcement learning from human feedback, the alignment technique behind ChatGPT. It connects to the workflows, prompts and tool stacks linked on this page, so you can move from definition to execution without leaving Onexial.

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