---
date: '2022-11-23T20:52:10'
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    - 2022.naacl-main.167.pdf
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  id: sxEWFGtwEe2_zFc3H2nb2Q
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  tags:
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  - NLProc
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    - exact: "Insum, notwithstanding prompt-based models\u2019impressive 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\u2019 use of task instructions."
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    source: https://aclanthology.org/2022.naacl-main.167.pdf
  text: 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
  updated: '2022-11-23T20:52:10.292273+00:00'
  uri: https://aclanthology.org/2022.naacl-main.167.pdf
  user: acct:ravenscroftj@hypothes.is
  user_info:
    display_name: James Ravenscroft
in-reply-to: https://aclanthology.org/2022.naacl-main.167.pdf
tags:
- prompt-models
- NLProc
- hypothesis
type: annotation
url: /annotation/2022/11/23/1669236730

---



 <blockquote>Insum, notwithstanding prompt-based models’impressive 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.</blockquote>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