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Notes -
It's not an unreasonable criticism in the abstract, but a few minutes of reading shows that it just doesn't apply in this case.
The higher score was published by Symbolica AI using Opus 4.6. So it couldn't be that Opus was retrained with the answers.
"This uses the same harness we previously published" so it couldn't be that they simply prompt the model with the answers.
The harness is published so you can see for yourself.
Benchmarks do not publish their entire problem set, so in general it's impossible for labs to simply "give the models the answers" to the problems that aren't published.
To be clear, I wasn't making the claim, it was a genuine question. I do recall reading stories in the past where the model creators basically cheated on benchmarks, but did not know if that was the case here or if it was a genuine improvement.
There's a fair bit of fudging, to be sure. Things like running your own model with different prompts or parameters, or just training to the test. But there's a limit. Since the actual ARC-AGI-3 test is not published, the only way companies could really "cheat" would be to sniff the data that's being fed into the models by the testers. While technically possible, that's pretty much Theranos-level fraud; I don't really suspect any AI company of doing this.
EDIT: Oops, I should have clicked the link. The 36% result was on the publicly available data, so it's not really an "official" result. For the reasons @sarker said, I still think it's fine, but it's not quite as bulletproof as I thought.
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