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---
date: '2023-01-29T10:53:23'
hypothesis-meta:
created: '2023-01-29T10:53:23.198884+00:00'
document:
title:
- 2301.11305.pdf
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id: JoZDmp_DEe2QSbcSZI0WEA
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incontext: https://hyp.is/JoZDmp_DEe2QSbcSZI0WEA/arxiv.org/pdf/2301.11305.pdf
json: https://hypothes.is/api/annotations/JoZDmp_DEe2QSbcSZI0WEA
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tags:
- chatgpt
- detecting gpt
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- exact: We find that supervised detectors can provide similardetection performance
to DetectGPT on in-distribution datalike English news, but perform significantly
worse than zero-shot methods in the case of English scientific writing andfail
altogether for German writing. T
prefix: 'm each dataset for evalua-tion. '
suffix: his finding echoes pastwork show
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source: https://arxiv.org/pdf/2301.11305.pdf
text: supervised detection methods fail on out of domain examples whereas detectgpt
seems to be robust to changes in domain.
updated: '2023-01-29T10:53:23.198884+00:00'
uri: https://arxiv.org/pdf/2301.11305.pdf
user: acct:ravenscroftj@hypothes.is
user_info:
display_name: James Ravenscroft
in-reply-to: https://arxiv.org/pdf/2301.11305.pdf
tags:
- chatgpt
- detecting gpt
- hypothesis
type: annotation
url: /annotations/2023/01/29/1674989603
---
<blockquote>We find that supervised detectors can provide similardetection performance to DetectGPT on in-distribution datalike English news, but perform significantly worse than zero-shot methods in the case of English scientific writing andfail altogether for German writing. T</blockquote>supervised detection methods fail on out of domain examples whereas detectgpt seems to be robust to changes in domain.