
The Simplest Step That Makes LLMs Actually Useful
Before you reach for RLHF, before you design a reward model, before you start thinking about reinforcement learning from verifiable rewards — there’s a more fundamental question worth asking: has
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Before you reach for RLHF, before you design a reward model, before you start thinking about reinforcement learning from verifiable rewards — there’s a more fundamental question worth asking: has

Before you reach for RLHF, before you design a reward model, before you start thinking about reinforcement learning from verifiable rewards — there’s a more fundamental question worth asking: has this model been properly fine-tuned on examples of the behavior you want? Supervised Fine-Tuning (SFT) sits between pre-training and the
