alt Hacker NewsOkay, I see, you're expecting Jev to properly give 1/6 probability for each option. This is different from my intuition of how LLMs work, where their probabilities don't really work like this (I would expect LLM to also do something like 0.83 for 1).
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maayank • today at 5:20 PM
Jev and LLMs give other promises. Jev's RLCD training aims to make its probabilities calibrated such that given many cases where it assigns label Y about X% probability, Y should be the correct label about X% of the time.
That's right. It's normal behavior of LLMs. But what matters is TypeSafe argues it's different exactly on this point. The selling point of Jev is "calibrated probabilities", so I checked it on probability problems.