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Language fashions prompted with a person description or persona are getting used to foretell the person\u2019s preferences and opinions. Nonetheless, current approaches to constructing personas principally depend on a person\u2019s demographic attributes and\/or prior judgments, however not on any underlying reasoning behind a person\u2019s judgments. We introduce PB&J (Psychology of Habits and Judgments), a framework that improves LM personas by incorporating potential rationales for why the person may have made a sure judgment. Our rationales are generated by a language mannequin to explicitly motive a few person\u2019s habits on the idea of their experiences, persona traits, or beliefs. Our methodology employs psychological scaffolds: structured frameworks such because the Massive 5 Persona Traits or Primal World Beliefs to assist floor the generated rationales in current theories. Experiments on public opinion and film choice prediction duties show that language mannequin personas augmented with PB&J rationales constantly outperform personas conditioned solely on person demographics and \/ or judgments, together with people who use a mannequin\u2019s default chain-of-thought, which isn’t grounded in psychological theories. Moreover, our PB&J personas carry out competitively with these utilizing human-written rationales, suggesting the potential of artificial rationales guided by current theories.<\/p>\n
Language fashions prompted with a person description or persona are getting used to foretell the person\u2019s preferences and opinions. Nonetheless, current approaches to constructing personas principally depend on a person\u2019s demographic attributes and\/or prior judgments, however not on any underlying reasoning behind a person\u2019s judgments. We introduce PB&J (Psychology of Habits and Judgments), a framework […]<\/p>\n","protected":false},"author":2,"featured_media":8147,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[55],"tags":[1467,634,358,705,6142,6141,6143],"class_list":["post-8145","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-machine-learning","tag-improving","tag-language","tag-model","tag-personas","tag-psychological","tag-rationalization","tag-scaffolds"],"_links":{"self":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts\/8145","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=8145"}],"version-history":[{"count":1,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts\/8145\/revisions"}],"predecessor-version":[{"id":8146,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/posts\/8145\/revisions\/8146"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=\/wp\/v2\/media\/8147"}],"wp:attachment":[{"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8145"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8145"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/techtrendfeed.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8145"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}