this post was submitted on 15 May 2024
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[–] Amoeba_Girl@awful.systems 171 points 6 months ago (149 children)

From Re-evaluating GPT-4’s bar exam performance (linked in the article):

First, although GPT-4’s UBE score nears the 90th percentile when examining approximate conversions from February administrations of the Illinois Bar Exam, these estimates are heavily skewed towards repeat test-takers who failed the July administration and score significantly lower than the general test-taking population.

Ohhh, that is sneaky!

[–] Amoeba_Girl@awful.systems 125 points 6 months ago (146 children)

What I find delightful about this is that I already wasn't impressed! Because, as the paper goes on to say

Moreover, although the UBE is a closed-book exam for humans, GPT-4’s huge training corpus largely distilled in its parameters means that it can effectively take the UBE “open-book”

And here I was thinking it not getting a perfect score on multiple-choice questions was already damning. But apparently it doesn't even get a particularly good score!

[–] EatATaco@lemm.ee 4 points 6 months ago (56 children)

Why is that a criticism? This is how it works for humans too: we study, we learn the stuff, and then try to recall it during tests. We've been trained on the data too, for neither a human nor an ai would be able to do well on the test without learning it first.

This is part of what makes ai so "scary" that it can basically know so much.

[–] exanime 11 points 6 months ago (2 children)

Because a machine that "forgets" stuff it reads seems rather useless... considering it was a multiple choice style exam and, as a machine, Chat GPT had the book entirely memorized, it should have scored perfect almost all the time.

[–] EatATaco@lemm.ee 0 points 6 months ago (2 children)

Chat GPT had the book entirely memorized

I feel like this exposes a fundamental misunderstanding of how LLMs are trained.

[–] TachyonTele@lemm.ee 12 points 6 months ago (2 children)

They're auto complete machines. All they fundamentally do is match words together. If it was trained on the answers and still couldn't reproduce the correct word matches, it failed.

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