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Most recently there have been attempts to in-clude vision-based embeddings in these mod-els (G ̈unther et al., 2020b), using the linear ar-chitecture  implemented  in  theCAOSSmodel.In  the  present  paper,  we  extend  this  line  ofresearch and demonstrate that moving to non-linear models improves the results for visionwhile linear models are a good choice for text.Simply concatenating text and vision vectorsdoes not currently (yet) improve the predictionof  human  behavioral  data  over  models  usingtext- and vision-based measures separately.</p>"}},{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"Date Submitted: 2021-08-15"}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Computer and Information 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