{"id":"https://openalex.org/W7163388584","doi":"https://doi.org/10.48550/arxiv.2606.02789","title":"Diagnosis of Human Object Interaction Detectors for Real World Educational Applications","display_name":"Diagnosis of Human Object Interaction Detectors for Real World Educational Applications","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7163388584","doi":"https://doi.org/10.48550/arxiv.2606.02789"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.02789","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02789","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2606.02789","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120026098","display_name":"Divya Mereddy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mereddy, Divya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119050859","display_name":"Ashwin Tudur Sadashiva","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sadashiva, Ashwin Tudur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035863735","display_name":"Marcos Qui\u00f1ones-Grueiro","orcid":"https://orcid.org/0000-0001-5391-6774"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Quinones-Grueiro, Marcos","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137744797","display_name":"Gautam Biswas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Biswas, Gautam","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.5716000199317932,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.5716000199317932,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.16509999334812164,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.07360000163316727,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/benchmark","display_name":"Benchmark (surveying)","score":0.6664999723434448},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5005000233650208},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.44929999113082886},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.3928000032901764},{"id":"https://openalex.org/keywords/taxonomy","display_name":"Taxonomy (biology)","score":0.37770000100135803},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.35199999809265137}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7372000217437744},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6664999723434448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5060999989509583},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5005000233650208},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4675999879837036},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.44929999113082886},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.3928000032901764},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32339999079704285},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2614000141620636},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2556000053882599},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.02789","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02789","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2606.02789","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02789","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[{"score":0.7009952068328857,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Human-object":[0],"interaction":[1],"(HOI)":[2],"recognition":[3],"is":[4],"critical":[5],"for":[6,63,102,150],"automatically":[7],"analyzing":[8],"student":[9],"behavior":[10],"in":[11,31,72,157],"complex":[12,41],"educational":[13,65,159],"environments.":[14,160],"Although":[15],"state-of-the-art":[16],"(SOTA)":[17],"HOI":[18,56,90,105,155],"detectors":[19],"perform":[20],"well":[21],"on":[22,86,112],"benchmark":[23],"datasets,":[24],"their":[25,94],"performance":[26],"often":[27],"degrades":[28],"when":[29],"deployed":[30],"real-world":[32,64,158],"training":[33],"environments":[34],"due":[35],"to":[36,107,131],"domain-specific":[37],"objects,":[38],"occlusions,":[39],"and":[40,93],"visual":[42],"conditions.":[43],"In":[44],"this":[45,70,118],"paper,":[46],"we":[47,96],"introduce":[48],"a":[49,54,98,125],"diagnosis-driven":[50],"framework":[51],"that":[52,117],"integrates":[53],"triplet-level":[55],"error":[57,139],"taxonomy":[58],"with":[59],"error-factor":[60],"attribution":[61],"analysis":[62,88,149],"video":[66],"data.":[67],"We":[68],"study":[69],"problem":[71],"the":[73,108,113,121,144],"context":[74],"of":[75,89,124,146,154],"Critical":[76],"Care":[77],"Air":[78],"Transport":[79],"Team":[80],"(CCATT)":[81],"mixed-reality":[82],"medical":[83],"training.":[84],"Based":[85],"an":[87],"failure":[91],"modes":[92],"causes,":[95],"develop":[97],"diagnosis-informed":[99],"refinement":[100,135],"strategy":[101],"adapting":[103],"pretrained":[104,126],"models":[106,156],"target":[109],"domain.":[110],"Experiments":[111],"CCATT":[114],"dataset":[115],"show":[116],"approach":[119],"improves":[120],"macro-F1":[122],"score":[123],"CDN":[127],"model":[128],"from":[129],"48.6":[130],"90.2":[132],"through":[133],"targeted":[134,152],"guided":[136],"by":[137],"diagnosed":[138],"factors.":[140],"These":[141],"results":[142],"highlight":[143],"value":[145],"detailed":[147],"diagnostic":[148],"informing":[151],"adaptation":[153]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-04T00:00:00"}