alt Hacker NewsThis showdown benchmark was and still is great, but an enormous grain of salt should be added to any model that was released after the showdown benchmark itself.
Maybe everyone has a different dose of skepticism. Personally I'm not even looking at results for models that were released after the benchmark, for all this tells us, they might as well be one-trick ponies that only do well in the benchmark.
It might be too much work, but one possible "correct" approach for this kind of benchmark would to periodically release new benchmarks with new tests (that are broadly in the same categories) and only include models that predate each benchmark.
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You don't need skepticism, because even if you're acting in 100% good faith and building a new model, what's the first thing you're going to do? You're going to go look up as many benchmarks as you can find and see how it does on them. It gives you some easy feedback relative to your peers. The fact that your own model may end up being put up against these exact tests is just icing.
So I don't think there's even a question of whether or not newer models are going to be maximizing for benchmarks - they 100% are. The skepticism would be in how it's done. If something's not being run locally, then there's an endless array of ways to cheat - like dynamically loading certain LoRAs in response to certain queries, with some LoRAs trained precisely to maximize benchmark performance. Basically taking a page out of the car company playbook in response to emissions testing.
But I think maximizing the general model itself to perform well on benchmarks isn't really unethical or cheating at all. All you're really doing there is 'outsourcing' part of your quality control tests. But it simultaneously greatly devalues any benchmark, because that benchmark is now the goal.
I think training image models to pass these very specific tests correctly will be very difficult for any of these companies. How would they even do that?
Yeah that’s a classic problem, and it's why good tests are such closely guarded secrets: to keep them from becoming training fodder for the next generation of models. Regarding the "model date" vs "benchmark date" - that's an interesting point... I'll definitely look into it!
I don't have any captcha systems in place, but I wonder if it might be worth putting up at least a few nominal roadblocks (such as Anubis [1]) to at least slow down the scrapers.
A few weeks ago I actually added some new, more challenging tests to the GenAI Text-to-Image section of the site (the “angelic forge” and “overcrowded flat earth”) just to keep pace with the latest SOTA models.
In the next few weeks, I’ll be adding some new benchmarks to the Image Editing section as well~~
[1] - https://anubis.techaro.lol