Well, it’s up to the user or post-trainer of the LLM what they believe to be above average. Then they can design around that. In the case of real world LLMs an

Well, it’s up to the user or post-trainer of the LLM what they believe to be above average. Then they can design around that. In the case of real world LLMs and post-training, what is above average is defined roughly as: labeled good by expert humans, and scoring high on RL environments related to coding like debugging, passing tests, or running efficiently and verifiably correctly.