{"id":"https://openalex.org/W7172334126","doi":"https://doi.org/10.48550/arxiv.2607.29602","title":"FriendBench: Benchmarking Dyadic Familiarity Inference in Humans and Multimodal Large Language Models","display_name":"FriendBench: Benchmarking Dyadic Familiarity Inference in Humans and Multimodal Large Language Models","publication_year":2026,"publication_date":"2026-07-31","ids":{"openalex":"https://openalex.org/W7172334126","doi":"https://doi.org/10.48550/arxiv.2607.29602"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.29602","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.29602","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.29602","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078452888","display_name":"Jeffrey M. Girard","orcid":"https://orcid.org/0000-0002-7359-3746"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Girard, Jeffrey M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144299491","display_name":"Jason Z. Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Jason Z.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144246354","display_name":"Jacqueline R. Vertino","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vertino, Jacqueline R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092046712","display_name":"Antony D\u2019Avirro","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"D'Avirro, Antony","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5144276845","display_name":"Benjamin Peloquin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peloquin, Benjamin","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/T10667","display_name":"Emotion and Mood Recognition","score":0.11420000344514847,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.11420000344514847,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10709","display_name":"Social Robot Interaction and HRI","score":0.10589999705553055,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.09719999879598618,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7145000100135803},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6789000034332275},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5834000110626221},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.51910001039505},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.426800012588501},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4205000102519989}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7145000100135803},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6789000034332275},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6370000243186951},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5834000110626221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5548999905586243},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.51910001039505},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5049999952316284},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.426800012588501},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3813000023365021},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.37689998745918274},{"id":"https://openalex.org/C2993724205","wikidata":"https://www.wikidata.org/wiki/Q315","display_name":"Human language","level":2,"score":0.3686000108718872},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3296999931335449},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2992999851703644},{"id":"https://openalex.org/C130064352","wikidata":"https://www.wikidata.org/wiki/Q853725","display_name":"Social relation","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C30539005","wikidata":"https://www.wikidata.org/wiki/Q1066689","display_name":"Human communication","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.29602","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.29602","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.29602","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.29602","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6425948739051819,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reading":[0],"a":[1,14,30,34],"social":[2],"situation":[3],"often":[4],"depends":[5],"on":[6,86,127],"behavior,":[7],"not":[8,113],"words":[9],"alone.":[10],"We":[11,131],"introduce":[12],"FriendBench,":[13],"benchmark":[15],"for":[16],"inferring":[17],"whether":[18],"two":[19,100],"people":[20],"are":[21,25,83],"already":[22],"familiar":[23],"or":[24],"meeting":[26],"as":[27],"strangers,":[28],"from":[29,65,124],"20-second":[31],"clip":[32],"of":[33,44,50,129],"dyadic":[35],"ice-breaker":[36],"conversation.":[37],"Every":[38],"pair":[39],"answers":[40],"the":[41,48,54,80,99,103,133],"same":[42],"type":[43],"prompt,":[45],"so":[46],"only":[47,121],"manner":[49],"interaction":[51],"can":[52],"reveal":[53],"answer.":[55],"Across":[56],"text,":[57],"audio,":[58],"and":[59,79,120,137],"video,":[60],"we":[61],"compare":[62],"26":[63],"models":[64,105],"seven":[66],"companies":[67],"against":[68],"matched":[69],"human":[70,81,135],"panels":[71],"over":[72],"96":[73],"balanced":[74,97],"dyads.":[75],"The":[76],"best":[77],"model":[78,138],"crowd":[82],"statistically":[84],"indistinguishable":[85],"accuracy":[87],"in":[88,110],"every":[89],"modality,":[90],"but":[91],"reach":[92],"it":[93],"differently:":[94],"humans":[95,122],"stay":[96],"across":[98],"answers,":[101],"while":[102],"strongest":[104],"lean":[106],"toward":[107],"\"stranger\"---a":[108],"difference":[109],"effective":[111],"prior,":[112],"discrimination.":[114],"Richer":[115],"channels":[116],"help":[117],"both":[118],"unequally,":[119],"gain":[123],"visible":[125],"behavior":[126],"top":[128],"speech.":[130],"release":[132],"stimuli,":[134],"ratings,":[136],"predictions.":[139]},"counts_by_year":[],"updated_date":"2026-08-04T08:18:43.703281","created_date":"2026-08-04T00:00:00"}
