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brainsteam/content/annotations/2023/01/29/1674989844.md

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+---
+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
+
+---
+
+
+
+ <blockquote>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.</blockquote>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.