Does every preference-training method require a reward model?
No. Some approaches, including standard DPO, directly optimize preference comparisons without a separately trained explicit reward model or the classic PPO training loop.
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More FAQs in What is reinforcement learning with human feedback (RLHF)?
A rating can become feedback data, but RLHF requires a training process that turns feedback into optimization signals. Clicking a button does not itself update model parameters.
No. Feedback can discourage unsupported answers and improve some behaviors, but imperfect supervision and reward models can still leave confident mistakes and misleading outputs.
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