What is Human Feedback (RLHF)?
A training method where human preferences or corrections are used to align and improve AI model behavior.
More about Human Feedback (RLHF):
Human Feedback (RLHF) stands for Reinforcement Learning from Human Feedback—a technique where AI models are trained using ratings, corrections, or preferences provided by human annotators. RLHF is used to fine-tune LLMs for safer, more helpful, and aligned responses in chatbots, agents, and guardrails enforcement.
RLHF is foundational for building ethical AI, improving performance in system prompts, and handling ambiguous or value-laden queries.
Frequently Asked Questions
Why is RLHF important for LLMs and agents?
It helps align models with human values and societal expectations, improving safety and usefulness.
How is human feedback collected for RLHF?
Through ratings, corrections, or preference comparisons given by human reviewers on model outputs.
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