I’m not holding them to a standard of “being careful”, I’m assuming they’re interested in the metrics they’re evaluating. I mentioned in another comment that each task in the benchmark takes ~90 minutes, depending on the model being tested. OpenAI says to answer one question it found two zero-days and performed a series of privilege escalations and moved across their network before hacking HF. Was that in 90 minutes, flying under the radar, or was there zero metrics being noticed for however long it took to do all that? No chart on a wall showing them the actual metrics they’re evaluating? Okay, then how about anomaly detection of any form? Taking days to perform a 90 minute task or using millions of tokens and multiple instance hand-offs on a question that other instances completed for far less time/tokens?

Consider any metric they would necessarily be tracking while it performs the evaluation. Assume they’re total assholes and only care about their marketing materials. Then narrow it down to those metrics that wouldn’t be off the scales while it discovered two zero-days in pursuit of implementing one known vulnerability. Was it the first run and they had no idea what to expect? Or did nobody notice that earlier runs completed in ### thousand tokens, but this run is off past ## million on one question, having to be compressed and handed off to new instances due to context limits, while it was in pursuit of publishing two new CVEs?

Assume they’re belligerent fools running a million benchmarks in parallel with nobody watching: there’s nothing to make them check or automatically pull the plug when it’s stuck in a loop, or did they set the threshold to 48 trillion tokens per question?

Those issues are what bugs me about it.