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2022.naacl-main.167.pdf
false __world__ false sxEWFGtwEe2_zFc3H2nb2Q
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https://hypothes.is/a/sxEWFGtwEe2_zFc3H2nb2Q https://hyp.is/sxEWFGtwEe2_zFc3H2nb2Q/aclanthology.org/2022.naacl-main.167.pdf https://hypothes.is/api/annotations/sxEWFGtwEe2_zFc3H2nb2Q
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acct:ravenscroftj@hypothes.is
acct:ravenscroftj@hypothes.is
group:__world__
acct:ravenscroftj@hypothes.is
prompt-models
NLProc
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1663 1398 TextPositionSelector
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Insum, notwithstanding prompt-based modelsimpressive improvement, we find evidence ofserious limitations that question the degree towhich such improvement is derived from mod-els understanding task instructions in waysanalogous to humans use of task instructions. ing prompts even at zero shots. 1 IntroductionSuppose a human is TextQuoteSelector
https://aclanthology.org/2022.naacl-main.167.pdf
although prompts seem to help NLP models improve their performance, the authors find that this performance is still present even when prompts are deliberately misleading which is a bit weird 2022-11-23T20:52:10.292273+00:00 https://aclanthology.org/2022.naacl-main.167.pdf acct:ravenscroftj@hypothes.is
display_name
James Ravenscroft
https://aclanthology.org/2022.naacl-main.167.pdf
prompt-models
NLProc
hypothesis
annotation /annotation/2022/11/23/1669236730
Insum, notwithstanding prompt-based modelsimpressive improvement, we find evidence ofserious limitations that question the degree towhich such improvement is derived from mod-els understanding task instructions in waysanalogous to humans use of task instructions.
although prompts seem to help NLP models improve their performance, the authors find that this performance is still present even when prompts are deliberately misleading which is a bit weird