AI / LLM Basics Interview Questions
Describe Reinforcement Learning from Human Feedback (RLHF)?
RLHF is a technique used to further align a model's behavior with human preferences, using human judgments as the training signal instead of a fixed dataset of correct answers.
- Human reviewers compare multiple model responses to the same prompt and rank which ones they prefer
- Those rankings are used to train a separate reward model that predicts how much a person would like a given response
- The main model is then further trained using reinforcement learning to produce responses that score highly according to that reward model
RLHF is a major reason modern LLMs feel noticeably more helpful, honest, and safe to interact with compared to a purely pretrained or instruction-tuned model alone.
What do human reviewers do in RLHF?
What is trained to predict how much a person would like a response?
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