4 ms·
> How do we make sure that the output is factual and not hallucinated? One method the readme doesn't mention: ask the same question multiple times. Apparently
by PoignardAzur 3y ago
> How do we make sure that the output is factual and not hallucinated?
One method the readme doesn't mention: ask the same question multiple times. Apparently research suggests that when LLMs hallucinate answers, their hallucination is likely to be a different one every time, where as factual answers will tend to be consistent.
https://arxiv.org/abs/2305.18248 https://arxiv.org/abs/2305.18248
- Davidzheng 3y agoPurely anecdotally this is not a very successful method in my usage To reproduce: I've had it be consistent on hallucinations on the stable homotopy groups of spheres; on the quote "who speaks of victory to endure is all"; and many other fact based questions. Model: gpt4
- deleted 3y ago[deleted]
- deleted 3y ago[deleted]
- AMICABoard 3y agoAsking repeatedly would be impractical. I have some vague idea in my mind called the fact engine. It's like a wiki where people could key in facts. Also facts based on "timeframes", ie 1800's 1900's etc (eg Moon Landing). The fact engine feeds a model that checks for hallucinations, and also rule based engines. Then a final score would be assigned based on consensus. Something like that.
- boppo1 3y agoAn encyclopedia with an api?
- AMICABoard 3y agoyes!
- bcjordan 3y agoThis does seem like where composable fine-tuning / memory-encoded knowledge graphs will end up. Couple related things in this direction that may be leveragable: - WikiData: https://m.wikidata.org/wiki/ https://m.wikidata.org/wiki/ - Knowledge Futures' Underlay: https://docs.underlay.org/history https://docs.underlay.org/history