diff --git a/brainsteam/content/annotations/2023/01/29/1674989844.md b/brainsteam/content/annotations/2023/01/29/1674989844.md new file mode 100644 index 0000000..35ea3a4 --- /dev/null +++ b/brainsteam/content/annotations/2023/01/29/1674989844.md @@ -0,0 +1,61 @@ +--- +date: '2023-01-29T10:57:24' +hypothesis-meta: + created: '2023-01-29T10:57:24.658922+00:00' + document: + title: + - 2301.11305.pdf + flagged: false + group: __world__ + hidden: false + id: tnNraJ_DEe2YBceDAVt0Uw + links: + html: https://hypothes.is/a/tnNraJ_DEe2YBceDAVt0Uw + incontext: https://hyp.is/tnNraJ_DEe2YBceDAVt0Uw/arxiv.org/pdf/2301.11305.pdf + json: https://hypothes.is/api/annotations/tnNraJ_DEe2YBceDAVt0Uw + permissions: + admin: + - acct:ravenscroftj@hypothes.is + delete: + - acct:ravenscroftj@hypothes.is + read: + - group:__world__ + update: + - acct:ravenscroftj@hypothes.is + tags: + - chatgpt + - detecting gpt + target: + - selector: + - end: 22349 + start: 22098 + type: TextPositionSelector + - exact: "Empirically, we find predictive entropy to be positively cor-related\ + \ with passage fake-ness more often that not; there-fore, this baseline uses\ + \ high average entropy in the model\u2019spredictive distribution as a signal\ + \ that a passage is machine-generated." + prefix: tropy) predictive distributions. + suffix: ' While our main focus is on zero' + type: TextQuoteSelector + source: https://arxiv.org/pdf/2301.11305.pdf + text: this makes sense and aligns with the [gltr](http://gltr.io) - humans add more + entropy to sentences by making unusual choices in vocabulary that a model would + not. + updated: '2023-01-29T10:57:24.658922+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/2023/01/29/1674989844 + +--- + + + +
Empirically, we find predictive entropy to be positively cor-related with passage fake-ness more often that not; there-fore, this baseline uses high average entropy in the model’spredictive distribution as a signal that a passage is machine-generated.
this makes sense and aligns with the [gltr](http://gltr.io) - humans add more entropy to sentences by making unusual choices in vocabulary that a model would not. \ No newline at end of file