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this post was submitted on 02 Nov 2026
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Science
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I'm surprised it's only 10%. I remember a couple of years ago I worked on a team trying to build an AI tool that, as a feature, could cite sources. I was skeptical then because gemini couldn't reliably cite correct sources on a google search, so what made our team so confident the OpenAI api version could do that? I mean, it still can't because it doesn't know where the information is coming from, and I'm sure getting it to double and triple check its work to get it right leads to it getting stuck in cycles.
The point is you need to treat AI "facts" as if your trivia buddy told you a fun fact. It sounds right and you trust that they looked it up at some point, but they're confidently incorrect at least a couple of times a trivia night so you shouldn't put money on it without fact checking yourself.
It doesn't 'know' anything, and getting it to, "triple check" itself is merely reinforcing those terms in the token space. These LLMs do not even begin to have the capacity to actually check their sources.
The only way it does work is to add extra algorithms that check correlation between output and source, and even then, you're still back in the realm of word weight association.
TL;DR - LLMs literally cannot do this.