{"id":"https://openalex.org/W7140753451","doi":"https://doi.org/10.48550/arxiv.2603.23933","title":"ORACLE: Orchestrate NPC Daily Activities using Contrastive Learning with Transformer-CVAE","display_name":"ORACLE: Orchestrate NPC Daily Activities using Contrastive Learning with Transformer-CVAE","publication_year":2026,"publication_date":"2026-03-25","ids":{"openalex":"https://openalex.org/W7140753451","doi":"https://doi.org/10.48550/arxiv.2603.23933"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.23933","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23933","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":null,"license_id":null,"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.2603.23933","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042742017","display_name":"Seongeun Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Seong-Eun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079382510","display_name":"Juyeong Hwang","orcid":"https://orcid.org/0009-0006-8057-2237"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hwang, JuYeong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004870172","display_name":"Ryunha Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, RyunHa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130679765","display_name":"HyeongYeop Kang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kang, HyeongYeop","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/T12290","display_name":"Human Motion and Animation","score":0.32820001244544983,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12290","display_name":"Human Motion and Animation","score":0.32820001244544983,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.12759999930858612,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.0689999982714653,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.6894000172615051},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5182999968528748},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4555000066757202},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.3813999891281128},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.37059998512268066},{"id":"https://openalex.org/keywords/activities-of-daily-living","display_name":"Activities of daily living","score":0.3359000086784363}],"concepts":[{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.6894000172615051},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6686999797821045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5293999910354614},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5182999968528748},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4555000066757202},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.43389999866485596},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42489999532699585},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.3813999891281128},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.37059998512268066},{"id":"https://openalex.org/C79544238","wikidata":"https://www.wikidata.org/wiki/Q423243","display_name":"Activities of daily living","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C29794715","wikidata":"https://www.wikidata.org/wiki/Q5362345","display_name":"Smartwatch","level":3,"score":0.2971000075340271},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C116865082","wikidata":"https://www.wikidata.org/wiki/Q1370241","display_name":"Interactive kiosk","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C48209547","wikidata":"https://www.wikidata.org/wiki/Q1331104","display_name":"Controllability","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.26460000872612}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.23933","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23933","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.23933","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23933","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.7442405819892883,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,23],"integration":[1],"of":[2,26,33,42,54,58,77,113,119,135,140,149,158,166],"Non-player":[3],"characters":[4],"(NPCs)":[5],"within":[6],"digital":[7,43,88],"environments":[8],"has":[9],"been":[10],"increasingly":[11],"recognized":[12],"for":[13,74],"its":[14,107],"potential":[15],"to":[16,39,65],"augment":[17],"user":[18],"immersion":[19],"and":[20,116,145,163],"cognitive":[21],"engagement.":[22],"sophisticated":[24],"orchestration":[25],"their":[27],"daily":[28,35,80,124],"activities,":[29],"reflecting":[30],"the":[31,40,56,75,91,104,111,117,130,137,146,156,164],"nuances":[32],"human":[34,60,123],"routines,":[36],"contributes":[37],"significantly":[38],"realism":[41],"environments.":[44],"Nevertheless,":[45],"conventional":[46],"approaches":[47],"often":[48],"produce":[49],"monotonous":[50],"repetition,":[51],"falling":[52],"short":[53],"capturing":[55],"intricacies":[57],"real":[59],"activity":[61,81,98,125,161],"plans.":[62],"In":[63],"response":[64],"this,":[66],"we":[67],"introduce":[68],"ORACLE,":[69],"a":[70],"novel":[71],"generative":[72,138],"model":[73],"synthesis":[76],"realistic":[78],"indoor":[79,97],"plans,":[82],"ensuring":[83],"NPCs'":[84],"authentic":[85],"presence":[86],"in":[87,103],"habitats.":[89],"Exploiting":[90],"CASAS":[92],"smart":[93],"home":[94],"dataset's":[95],"24-hour":[96],"sequences,":[99],"ORACLE":[100],"addresses":[101],"challenges":[102],"dataset,":[105],"including":[106],"imbalanced":[108],"sequential":[109,131],"data,":[110],"scarcity":[112],"training":[114,128],"samples,":[115],"absence":[118],"pre-trained":[120],"models":[121],"encapsulating":[122],"patterns.":[126],"ORACLE's":[127],"leverages":[129],"data":[132],"processing":[133],"prowess":[134],"Transformers,":[136],"controllability":[139],"Conditional":[141],"Variational":[142],"Autoencoders":[143],"(CVAE),":[144],"discriminative":[147],"refinement":[148],"contrastive":[150],"learning.":[151],"Our":[152],"experimental":[153],"results":[154],"validate":[155],"superiority":[157],"generating":[159],"NPC":[160],"plans":[162],"efficacy":[165],"our":[167],"design":[168],"strategies":[169],"over":[170],"existing":[171],"methods.":[172]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-27T00:00:00"}
