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OtomotOtoday at 8:34 AM3 repliesview on HN

> Then, by giving them context or by post-training, you can make them sample non-average parts of the distribution they learned.

How do you derive that something is "below average" or "average" or "above average"?


Replies

rytilltoday at 8:58 AM

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.

nextaccountictoday at 9:28 AM

> How do you derive that something is "below average" or "average" or "above average"?

One technique is RLHF: have an human expert assess it.

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u8080today at 12:15 PM

>How do you derive that something is "below average" or "average" or "above average"?

How do you? I mean, that was your point basis.