title: Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts
summary: Many cognitive approaches to well-being, such as recognizing and reframing
  unhelpful thoughts, have received considerable empirical support over the past
  decades, yet still lack truly widespread adoption in self-help format. A
  barrier to that adoption is a lack of adequately specific and diverse dedicated
  practice material. This work examines whether current language models can be
  leveraged to both produce a virtually unlimited quantity of practice material
  illustrating standard unhelpful thought patterns matching specific given
  contexts, and generate suitable positive reframing proposals. We propose
  PATTERNREFRAME, a novel dataset of about 10k examples of thoughts containing
  unhelpful thought patterns conditioned on a given persona, accompanied by about
  27k positive reframes. By using this dataset to train and/or evaluate current
  models, we show that existing models can already be powerful tools to help
  generate an abundance of tailored practice material and hypotheses, with no or
  minimal additional model training required.
paper_authors._id: 64a76c8525fa8d68ea96b7ea
paper_authors.name: Mounica Maddela
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-07-10T09:24:54.630Z
paper_authors._id: 62df15da528be032ecfd9bea
paper_authors.avatarUrl: /avatars/c6f55d4aba2dfde32662204dd199a510.svg
paper_authors.fullname: Mounica Maddela
paper_authors.type: user
paper_authors.user: mmaddela1005
paper_authors._id: 64a76c8525fa8d68ea96b7eb
paper_authors.name: Megan Ung
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-07-10T09:24:45.864Z
paper_authors._id: 63c6f88850cc81901da905f3
paper_authors.avatarUrl: /avatars/e75bb87af183aa5c3c5a7d09f2de1d60.svg
paper_authors.fullname: Megan Ung
paper_authors.type: user
paper_authors.user: meganung
paper_authors._id: 64a76c8525fa8d68ea96b7ec
paper_authors.name: Jing Xu
paper_authors._id: 64a76c8525fa8d68ea96b7ed
paper_authors.name: Andrea Madotto
paper_authors._id: 64a76c8525fa8d68ea96b7ee
paper_authors.name: Heather Foran
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-07-10T09:24:42.058Z
paper_authors._id: 64abab03329f5e6e78318cd7
paper_authors.avatarUrl: /avatars/1d752f894c128cc7999bf82979bc0e9f.svg
paper_authors.fullname: Heather Foran
paper_authors.type: user
paper_authors.user: hforan
paper_authors._id: 64a76c8525fa8d68ea96b7ef
paper_authors.name: Y-Lan Boureau
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-07-10T09:24:50.011Z
paper_authors._id: 64a82a24a1cd4978d49aa7cb
paper_authors.avatarUrl: /avatars/d7d7c3ad870541017551594bd30b6fde.svg
paper_authors.fullname: Y-Lan Boureau
paper_authors.type: user
paper_authors.user: notebleue
paper_title: Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts
paper_summary: Many cognitive approaches to well-being, such as recognizing and reframing
  unhelpful thoughts, have received considerable empirical support over the past
  decades, yet still lack truly widespread adoption in self-help format. A
  barrier to that adoption is a lack of adequately specific and diverse dedicated
  practice material. This work examines whether current language models can be
  leveraged to both produce a virtually unlimited quantity of practice material
  illustrating standard unhelpful thought patterns matching specific given
  contexts, and generate suitable positive reframing proposals. We propose
  PATTERNREFRAME, a novel dataset of about 10k examples of thoughts containing
  unhelpful thought patterns conditioned on a given persona, accompanied by about
  27k positive reframes. By using this dataset to train and/or evaluate current
  models, we show that existing models can already be powerful tools to help
  generate an abundance of tailored practice material and hypotheses, with no or
  minimal additional model training required.
paper_ai_summary: Existing language models can generate tailored cognitive practice material for well-being by using a new dataset of unhelpful thoughts and reframes, requiring minimal additional training.
paper_ai_keywords: language models practice material unhelpful thought patterns positive reframes dataset