How Language Model Hallucinations Can Snowball
A major risk of using language models in practical applications is their
tendency to hallucinate incorrect statements. Hallucinations are often
attributed to knowledge gaps in LMs, but we hypothesize that in some cases,
when justifying previously generated hallucinations, LMs output false claims
that they can separately recognize as incorrect. We construct three
question-answering datasets where ChatGPT and GPT-4 often state an incorrect
answer and offer an explanation with at least one incorrect claim. Crucially,
we find that ChatGPT and GPT-4 can identify 67% and 87% of their own mistakes,
respectively. We refer to this phenomenon as hallucination snowballing: an LM
over-commits to early mistakes, leading to more mistakes that it otherwise
would not make.
646d5e70bb95b5d4001df19f
Muru Zhang
admin_assigned
2023-05-24T13:39:14.401Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/61cc2cf4dcb47bd5ed3cd3b8/O-tDNhSPZCZQSQG_BaEG9.png
Muru Zhang
user
nanami
646d5e70bb95b5d4001df1a0
Ofir Press
646d5e70bb95b5d4001df1a1
William Merrill
646d5e70bb95b5d4001df1a2
Alisa Liu
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2023-05-24T13:39:52.972Z
62449da46b55ef458d430371
/avatars/b95954a88c7b15524a3d7776a4abe083.svg
Alisa Liu
user
alisawuffles
646d5e70bb95b5d4001df1a3
Noah A. Smith
How Language Model Hallucinations Can Snowball
A major risk of using language models in practical applications is their
tendency to hallucinate incorrect statements. Hallucinations are often
attributed to knowledge gaps in LMs, but we hypothesize that in some cases,
when justifying previously generated hallucinations, LMs output false claims
that they can separately recognize as incorrect. We construct three
question-answering datasets where ChatGPT and GPT-4 often state an incorrect
answer and offer an explanation with at least one incorrect claim. Crucially,
we find that ChatGPT and GPT-4 can identify 67% and 87% of their own mistakes,
respectively. We refer to this phenomenon as hallucination snowballing: an LM
over-commits to early mistakes, leading to more mistakes that it otherwise
would not make.
Language models frequently generate incorrect answers and offer false explanations, exacerbating errors due to a phenomenon called hallucination snowballing.
hallucinations knowledge gaps question-answering datasets ChatGPT GPT-4 hallucination snowballing early mistakes false explanations