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It's when the models outputs are connected to sources. So for example, you might have a company chatbot that responds with a summary of a Confluence page it wa
by papercrane 2mo ago
It's when the models outputs are connected to sources.
So for example, you might have a company chatbot that responds with a summary of a Confluence page it was trained on and a link to the source.
Doesn't eliminate hallucinations, but it does reduce them and gives you a chance to verify.
- stingraycharles 2mo agoI don’t think this is correct, as we’re talking about all online discourse being influenced by AI, and you don’t know what to trust anymore, rather than generating AI output yourself (which is what you are referring to).
- papercrane 2mo agoIn this context, it would mean building a knowledge base the model can link to that is considered authoritative. So maybe the LLM is has some slop in it's training, and that causes it to try and output some junk, but if it can't match it to it's verified ground-truth KB it doesn't end up outputting it. The problem is figuring out what is the authoritative sources.
- stingraycharles 2mo agoBut we're talking about AI writing and/or influencing other people's online discourse, not?
- ColdStream 2mo agoThat works ok until the citation material ends up with LLM output being fed in. Already there are many examples of this happening.
- papercrane 2mo agoYes, the trick is having a "ground-truth" KB it can link to, and trying to avoid citogensis from happening. I'm not sure if it's a technique that's every going to scale because of that.