Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts
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.
64a76c8525fa8d68ea96b7ea
Mounica Maddela
claimed_verified
2023-07-10T09:24:54.630Z
62df15da528be032ecfd9bea
/avatars/c6f55d4aba2dfde32662204dd199a510.svg
Mounica Maddela
user
mmaddela1005
64a76c8525fa8d68ea96b7eb
Megan Ung
claimed_verified
2023-07-10T09:24:45.864Z
63c6f88850cc81901da905f3
/avatars/e75bb87af183aa5c3c5a7d09f2de1d60.svg
Megan Ung
user
meganung
64a76c8525fa8d68ea96b7ec
Jing Xu
64a76c8525fa8d68ea96b7ed
Andrea Madotto
64a76c8525fa8d68ea96b7ee
Heather Foran
claimed_verified
2023-07-10T09:24:42.058Z
64abab03329f5e6e78318cd7
/avatars/1d752f894c128cc7999bf82979bc0e9f.svg
Heather Foran
user
hforan
64a76c8525fa8d68ea96b7ef
Y-Lan Boureau
claimed_verified
2023-07-10T09:24:50.011Z
64a82a24a1cd4978d49aa7cb
/avatars/d7d7c3ad870541017551594bd30b6fde.svg
Y-Lan Boureau
user
notebleue
Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts
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.
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.
language models practice material unhelpful thought patterns positive reframes dataset