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	<title>Reinforcement learning from human feedback (RLHF) - Revision history</title>
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	<updated>2026-09-15T06:37:11Z</updated>
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		<title>imported&gt;ALT-TEXT: Import: AI terminology and people glossary</title>
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		<updated>2026-09-07T10:36:21Z</updated>

		<summary type="html">&lt;p&gt;Import: AI terminology and people glossary&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;== Reinforcement learning from human feedback (RLHF) ==&lt;br /&gt;
A training technique in which human reviewers rate or rank an AI model&amp;#039;s outputs, and the model is adjusted to produce more of the highly rated responses and fewer of the poorly rated ones. RLHF is widely used to make [[Large language model (LLM)|large language models]] more helpful, less harmful, and more aligned with what users actually want, though it also embeds the values and judgement calls of whoever the reviewers are. (See also: [[AI alignment]], [[Large language model (LLM)|Large language model]])&lt;br /&gt;
&lt;br /&gt;
[[Category:Glossary]]&lt;br /&gt;
[[Category:Artificial Intelligence]]&lt;br /&gt;
[[Category:Machine Learning]]&lt;br /&gt;
[[Category:AI Ethics]]&lt;br /&gt;
&lt;/div&gt;</summary>
		<author><name>imported&gt;ALT-TEXT</name></author>
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