This is almost perfect. The gold standard for LLM evaluation would have the following qualities: 1. Categorized (e.g. coding, reasoning, general knowledge) 2. Multimodal (at least text and image) 3. Multiple difficulties (something like "GPT-4 saturates or scores >90%", a la MMLU, "GPT-4 scores 20-80%", and "GPT-4 scores 4. Hidden (under 10% of the dataset publicly available, enough methodological detail to inspire c…
> Hidden It's pretty absurd that it can be a criteria for a good benchmark. You should dismiss any paper (e.g. benchmark result) that isn't repeatable, and by definition closed testing dataset is not repeatable and in fact doesn't provide much insight anyway, you can as well call it arbitrary curated rating, like those that useless journalists do ("top 50 most influential women of all time"). Obviously, this contradi…
> I don't have a solution. I'm just saying this is complete bullshit, the idea that we are starting to exclaim "yay, hidden data! I can trust that!" just cannot be acceptable.
This feels just unkind. If you acknowledge that it's a hard (impossible?) problem, you should give some leeway to people doing their best until a consensus on the right approach(es) exists.