#gpt-3 #truth #conspiracy
A new benchmark paper has created quite an uproar in the community. TruthfulQA is a dataset of 817 questions probing for imitative falsehoods where language models become less truthful, the larger they get. This surprising counter-intuitive finding validates many people’s criticisms of large language models, but is it really the correct conclusion?
OUTLINE:
0:00 – Intro
0:30 – Twitter Paper Announcement
4:10 – Large Language Models are to blame!
5:50 – How was the dataset constructed?
9:25 – The questions are adversarial
12:30 – Are you surprised?!
Paper:
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