alt Hacker NewsThis is an interesting catalog of vulnerabilities, but I'm not sure how groundbreaking the main insight is.
Evaluating AI models has always relied largely on trust. If you want to game the benchmarks, you can. Simply train on your test data.
When an AI agent has autonomous control over the same computing environment where its scores are recorded, it's not surprising that it can, in principle, falsify its scores. A more interesting question would be whether agents behave in this way automatically, without manual tuning by the researcher.
That said, the main takeaway of "don't trust the number, trust the methodology" is valid. It's already a truism for researchers, and spreading the word to non-researchers is valuable.
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Yep. I think the idea that the benchmark is determinative is just as deluded as the notion that it should be unbreakable.
Benchmarks are on the honor system. Even the tightest benchmark can be cheated. If the benchmark is so secret and air-gapped that it can't be cheated by models, it can be cheated by its own authors. You can't use benchmarks to gate out cheating.
If you don't have the honor system in mind when you're reading scores, you're wasting your time. Is it some unknown outfit with wild claims? Is it connected to Epstein, Russia, the real estate "industry", or sleazeballing in general? Do they have previous history of ratgaming the numbers? Replace its scores with asterisks and move on.
> I'm not sure how groundbreaking the main insight is.
I think it likely is groundbreaking for a number of people (especially non-tech CTOs and VPs) who make decisions based on these benchmarks and who have never wondered what the scores are actually scoring.
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This isn't even training on the test data.
This is modifying the test code itself to always print "pass", or modifying the loss function computation to return a loss of 0, or reading the ground truth data and having your model just return the ground truth data, without even training on it.