
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

Researchers built a study to answer a question that sounds simple: can people tell whether a scientific abstract was written by an LLM or a human? The answer, for people with machine-learning expertise, was mostly: no. This result is interesting on its own. The implications for how we build annotation
