OpenAI just published a new paper on hallucinations in Language Models.
tldr: “Our new research paper (opens in a new window) argues that language models hallucinate because standard training and evaluation procedures reward guessing over acknowledging uncertainty.”
Wanted to start a new topic to dicuss this paper, and also some of the ways the community is working to reduce hallucinations in outputs, whether using the API or on ChatGPT.
I’ll start by saying that one common way I’ve seen discussed in general is to give the model an ‘out’, by allowing it to skip answering a question if it doesn’t know the answer, by specifiying in the prompt: “If you don’t know the answer, say so” (or some variation of this). This has yielded mixed results. What other ways have you been using to detect and reduce occurences of halucinations?
Reference Links:
Webpage: https://openai.com/index/why-language-models-hallucinate/
Paper: https://cdn.openai.com/pdf/d04913be-3f6f-4d2b-b283-ff432ef4aaa5/why-language-models-hallucinate.pdf