{"id":"https://openalex.org/W7112349552","doi":null,"title":"Can Neural Networks model the human perception of geometric shapes?","display_name":"Can Neural Networks model the human perception of geometric shapes?","publication_year":2025,"publication_date":"2025-10-28","ids":{"openalex":"https://openalex.org/W7112349552"},"language":null,"primary_location":{"id":"pmh:oai:share.osf.io:e095edc6-fea3-4624-806a-e978f038faa4","doi":null,"is_oa":true,"landing_page_url":"https://osf.io/sfb8e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401687","display_name":"PsyArXiv (OSF Preprints)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2799848540","host_organization_name":"Center for Open Science","host_organization_lineage":["https://openalex.org/I2799848540"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"volume":null,"type":"preprint","indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://osf.io/sfb8e","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074529317","display_name":"Mathias Sabl\u00e9-Meyer","orcid":"https://orcid.org/0000-0003-0844-0775","observed_orcids":["https://orcid.org/0000-0003-0844-0775"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mathias Sabl\u00e9-Meyer","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059697591","display_name":"Yair Lakretz","orcid":"https://orcid.org/0000-0001-8774-6427","observed_orcids":["https://orcid.org/0000-0001-8774-6427"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yair Lakretz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075892407","display_name":"Stanislas Dehaene","orcid":"https://orcid.org/0000-0002-7418-8275","observed_orcids":["https://orcid.org/0000-0002-7418-8275"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stanislas Dehaene","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116185304","display_name":"Maxence Pajot","orcid":"https://orcid.org/0009-0001-3331-9128","observed_orcids":["https://orcid.org/0009-0001-3331-9128"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maxence Pajot","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5025278218","display_name":"Th\u00e9o Morfoisse","orcid":"https://orcid.org/0009-0003-5698-5224","observed_orcids":["https://orcid.org/0009-0003-5698-5224"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Th\u00e9o Morfoisse","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10427","display_name":"Visual perception and processing mechanisms","score":0.4507000148296356,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10427","display_name":"Visual perception and processing mechanisms","score":0.4507000148296356,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.33469998836517334,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.03720000013709068,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8460000157356262},{"id":"https://openalex.org/keywords/vision-transformer","display_name":"vision transformer","score":0.996999979019165},{"id":"https://openalex.org/keywords/geometric-drawing","display_name":"geometric drawing","score":0.5709999799728394},{"id":"https://openalex.org/keywords/training-set-size","display_name":"training data size","score":0.7910000085830688},{"id":"https://openalex.org/keywords/symbolic-geometry","display_name":"symbolic geometry","score":0.5519999861717224}],"concepts":[{"id":"https://openalex.org/C151756577","wikidata":"https://www.wikidata.org/wiki/Q36810","display_name":"Quadrilateral","level":3,"score":0.67330002784729},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6611999869346619},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6570000052452087},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.620199978351593},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6176000237464905},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5713000297546387},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.5424000024795532},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5131999850273132},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4611999988555908},{"id":"https://openalex.org/C104065381","wikidata":"https://www.wikidata.org/wiki/Q1002535","display_name":"Geometric modeling","level":2,"score":0.39959999918937683},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C32990609","wikidata":"https://www.wikidata.org/wiki/Q306542","display_name":"Transformation geometry","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C49777392","wikidata":"https://www.wikidata.org/wiki/Q5535495","display_name":"Geometric networks","level":3,"score":0.2946999967098236},{"id":"https://openalex.org/C181095308","wikidata":"https://www.wikidata.org/wiki/Q1541599","display_name":"Geometric primitive","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27469998598098755},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2621999979019165},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.2565000057220459}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:share.osf.io:e095edc6-fea3-4624-806a-e978f038faa4","doi":null,"is_oa":true,"landing_page_url":"https://osf.io/sfb8e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401687","display_name":"PsyArXiv (OSF Preprints)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2799848540","host_organization_name":"Center for Open Science","host_organization_lineage":["https://openalex.org/I2799848540"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:share.osf.io:e095edc6-fea3-4624-806a-e978f038faa4","doi":null,"is_oa":true,"landing_page_url":"https://osf.io/sfb8e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401687","display_name":"PsyArXiv (OSF Preprints)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2799848540","host_organization_name":"Center for Open Science","host_organization_lineage":["https://openalex.org/I2799848540"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Artificial":[0],"neural":[1,111,154,190],"networks":[2,112,135,191],"achieve":[3],"impressive":[4],"success":[5],"in":[6,27,44,52,71,92],"many":[7],"vision":[8],"tasks.":[9],"Nevertheless,":[10],"previous":[11],"work":[12],"has":[13],"suggested":[14],"that":[15,181,199],"their":[16],"representation":[17],"of":[18,35,61,139,160,172,174,185,195,204,210],"geometric":[19,54,82,100,132,196,211],"shapes":[20,83],"only":[21],"partially":[22],"captures":[23],"the":[24,42,59,89,134,143,146,158,161,170,175,186,207],"representations":[25,87,114,156,194,209],"found":[26,91],"humans,":[28],"who":[29],"additionally":[30],"require":[31],"a":[32,124,128,166,182],"symbolic":[33,125],"\u201clanguage":[34],"geometry\u201d.":[36],"In":[37,94,127],"this":[38,45],"study,":[39],"we":[40],"evaluate":[41],"progress":[43],"area":[46],"by":[47,104],"systematically":[48],"comparing":[49],"human":[50,120,140,152,208],"performance":[51,121],"three":[53,144],"shape":[55,101],"perception":[56],"tests,":[57],"with":[58],"predictions":[60],"recent":[62,110],"Convolutional":[63],"Neural":[64],"Networks":[65],"(CNNs)":[66],"and":[67,75,80,84,99,118,153],"Vision":[68],"Transformers,":[69],"varying":[70],"size,":[72],"training":[73,76,162,187],"datasets":[74],"methods,":[77],"to":[78,88,116],"recognize":[79],"process":[81],"compare":[85],"these":[86],"ones":[90],"humans.":[93],"two":[95],"tasks":[96],"probing":[97],"quadrilateral":[98],"perception,":[102],"introduced":[103],"Sable-Meyer":[105],"et":[106],"al.":[107],"(2022,":[108],"2025),":[109],"exhibit":[113],"similar":[115],"humans":[117],"predict":[119],"better":[122],"than":[123,165],"model.":[126,176],"third":[129],"task,":[130],"involving":[131],"drawings,":[133],"still":[136,201],"fell":[137],"short":[138,203],"performance.":[141],"Across":[142],"experiments,":[145],"main":[147],"factor":[148],"driving":[149],"similarity":[150],"between":[151],"network":[155],"was":[157],"size":[159],"dataset,":[163],"rather":[164],"specific":[167],"architecture":[168],"or":[169],"number":[171],"parameters":[173],"Together,":[177],"our":[178],"results":[179],"show":[180],"massive":[183],"scaling-up":[184],"data":[188],"helps":[189],"approximate":[192],"human-like":[193],"shapes,":[197],"but":[198],"they":[200],"fall":[202],"fully":[205],"capturing":[206],"shape.":[212]},"counts_by_year":[],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2025-12-10T00:00:00"}