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Posted by daigoba66 3 days ago

The case for zero-error horizons in trustworthy LLMs(arxiv.org)
79 points | 115 commentspage 3
simianwords 3 days ago|
There’s no way this is right. I checked complicated ones with the latest thinking model. Can someone come up with a counter example?

Edit: here’s what I tried https://chatgpt.com/share/69cebb52-56a8-838f-969c-c47308262a...

stratos123 3 days ago||
Did you use the exact API call shown in the paper? I am unable to replicate the paper's counterexamples via the chat UI, but that's not very surprising (if the LLM already only fails a few cases out of thousands, the small differences in context between API and chat might fix them).
simianwords 3 days ago||
I tried this https://chatgpt.com/share/69cebb52-56a8-838f-969c-c47308262a...
pton_xd 3 days ago||
"in this paper we primarily evaluate the LLM itself without external tool calls."

Maybe this is a factor?

simianwords 3 days ago||
No tools were used.
chromacity 3 days ago||
IIRC, web chat often uses tools / code without surfacing this information in any obvious way.
bigstrat2003 3 days ago||
Let us be very clear: there is no such thing as a trustworthy LLM. Time and again they have shown that they understand nothing. They can be useful in the right context, but you can't trust them at all.
parliament32 3 days ago|
> This is surprising given the excellent capabilities of GPT-5.2

The real surprise is that someone writing a paper on LLMs doesn't understand the baseline capabilities of a hallucinatory text generator (with tool use disabled).

coldtea 3 days ago|
The real suprise is people saying it's surprising when researchers and domain experts state something the former think goes against common sense/knowledge - as if they got them, and those researcers didn't already think their naive counter-argument already.