[keiferski]

No it was just an anthology of papers by a reasonably well-known academic.

The problem is more that instead of reasoning and realizing it didn’t actually know about the book, it just looked up a description of the author and then invented what this book was supposedly about based on the title.

A more intelligent reply would have been something like, “the author appears to be an academic in international relations, but I cannot find this exact book title.” Instead it just repeatedly gave me fake answers.

[i_think_so]

Is that problem even fixable with what one might call normal means?

I presume it can't be with mere prompting, otherwise every single model would already include "Don't lie and don't make things up. If you don't know an answer, just say so."

It seems to me that the underlying algorithms would be inclined to confabulate simply because that's what LLMs do. But that's a bit beyond my math and programming understanding to say for certain.

[keiferski]

Yeah I don’t know enough about LLMs to answer; it seems simple enough to make it check if X exists before pontificating about it. But maybe it isn’t, and there is a reason why.

[i_think_so]

The problem seems to be that if the LLM doesn't know if X exists it is unable to distinguish that from simply needing to create an answer about X.

That's the typical logic flow, innit?