reward model
FDE interview questions tagged reward model, across every topic.
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Concepts behind "reward model"
The curriculum that explains the ideas these questions test.
Core
RLHF (Alignment)RLHF aligns a model to human preferences in three stages: supervised fine-tuning on demonstrations, training a reward model from human comparisons of outputs, then optimizing the policy with RL against that reward while a KL penalty anchors it to the base model. It shapes behavior and tone rather than facts, and FDE loops probe it because reward hacking and the KL anchor are where deployments actually go wrong.🧠 Foundations of LLMs & GenAISign in
Core
Reward ModelsA reward model scores a candidate output by how much a human would prefer it, learned from pairwise comparisons rather than absolute ratings. It is the signal that drives RLHF, ranks best-of-N samples, and guides test-time search, which is why FDE loops probe how it is trained, where it leaks, and the outcome-versus-process distinction.🧠 Foundations of LLMs & GenAISign in