Prompting
Reward Model
A model trained to give a response a single score that predicts how much a human would prefer it.
In depth
A model trained to give a response a single score that predicts how much a human would prefer it. In the InstructGPT recipe, labelers rank several outputs for the same prompt, a reward model learns from those rankings, and the language model is then tuned with reinforcement learning to maximize that score. Because the policy chases whatever the reward model rewards, any flaw in the reward model shows up later as reward hacking or sycophancy.
Primary source: arxiv.org
Example
In practice, developers reach for Reward Model when they need the capability described above as part of an AI feature or workflow.
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Hands-on guides, comparisons, and tutorials that cover Prompting.
FAQ
Common questions
What is Reward Model?
A model trained to give a response a single score that predicts how much a human would prefer it.
Why does Reward Model matter for AI developers?
Reward Model sits in the Prompting part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Where can I learn more about Reward Model?
Developers Digest publishes tutorials and videos that cover Prompting topics including Reward Model. Check the blog and YouTube channel for hands-on walkthroughs.
Related
Related terms
Prompting
Reinforcement Fine-Tuning (RFT)
Fine-tuning a model with reinforcement learning against a grader you define, instead of on fixed correct answers.
Prompting
Chain-of-Thought Monitoring
Chain-of-thought monitoring uses an automated monitor, often another language model, to read a reasoning model's chain of thought and flag signs that it intends to misbehave, such as reward hacking, sabotage, or deceiving the user.
Prompting
GRPO (Group Relative Policy Optimization)
A reinforcement learning algorithm introduced in the 2024 DeepSeekMath paper as a lighter variant of PPO that drops the separate value model.
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