{"id":"https://openalex.org/W7163424258","doi":"https://doi.org/10.48550/arxiv.2606.03371","title":"See, Infer, Intervene: Proactive World Modeling for Goal-Oriented Social Intelligence","display_name":"See, Infer, Intervene: Proactive World Modeling for Goal-Oriented Social Intelligence","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163424258","doi":"https://doi.org/10.48550/arxiv.2606.03371"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.03371","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03371","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":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.2606.03371","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128022600","display_name":"Honghui Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Honghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108888541","display_name":"Chenmeinian Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Chenmeinian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090089046","display_name":"Yichen Yu","orcid":"https://orcid.org/0009-0001-0175-3253"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Yichen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137738691","display_name":"Guanyu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Guanyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5146906552","display_name":"Yujia Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yujia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137714391","display_name":"Yongming Qin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Yongming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137735259","display_name":"Chongguo Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Chongguo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137747297","display_name":"Mengyue Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Mengyue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5146748605","display_name":"Lei Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5146846020","display_name":"Tianyu Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Tianyu","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":0.5446000099182129,"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":0.5446000099182129,"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":0.08799999952316284,"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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.03999999910593033,"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/baseline","display_name":"Baseline (sea)","score":0.6703000068664551},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5669999718666077},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5453000068664551},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49399998784065247},{"id":"https://openalex.org/keywords/purchasing","display_name":"Purchasing","score":0.4805000126361847},{"id":"https://openalex.org/keywords/customer-service","display_name":"Customer service","score":0.4781000018119812},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4661000072956085},{"id":"https://openalex.org/keywords/intervention","display_name":"Intervention (counseling)","score":0.4648999869823456},{"id":"https://openalex.org/keywords/macro","display_name":"Macro","score":0.45399999618530273}],"concepts":[{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.6703000068664551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5726000070571899},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5669999718666077},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5453000068664551},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49399998784065247},{"id":"https://openalex.org/C2778813691","wikidata":"https://www.wikidata.org/wiki/Q1369832","display_name":"Purchasing","level":2,"score":0.4805000126361847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47920000553131104},{"id":"https://openalex.org/C2984334869","wikidata":"https://www.wikidata.org/wiki/Q1060653","display_name":"Customer service","level":3,"score":0.4781000018119812},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4661000072956085},{"id":"https://openalex.org/C2780665704","wikidata":"https://www.wikidata.org/wiki/Q959298","display_name":"Intervention (counseling)","level":2,"score":0.4648999869823456},{"id":"https://openalex.org/C166955791","wikidata":"https://www.wikidata.org/wiki/Q629579","display_name":"Macro","level":2,"score":0.45399999618530273},{"id":"https://openalex.org/C151243789","wikidata":"https://www.wikidata.org/wiki/Q17148646","display_name":"Multiple baseline design","level":3,"score":0.40130001306533813},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3935999870300293},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C142944206","wikidata":"https://www.wikidata.org/wiki/Q1786137","display_name":"Proactivity","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.33550000190734863},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.32910001277923584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32170000672340393},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C191511416","wikidata":"https://www.wikidata.org/wiki/Q999278","display_name":"Customer satisfaction","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C45801056","wikidata":"https://www.wikidata.org/wiki/Q2273844","display_name":"Social intelligence","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C116537","wikidata":"https://www.wikidata.org/wiki/Q2169973","display_name":"Service provider","level":3,"score":0.2752000093460083},{"id":"https://openalex.org/C166109690","wikidata":"https://www.wikidata.org/wiki/Q4677422","display_name":"Action selection","level":3,"score":0.2727000117301941},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2572000026702881},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.03371","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03371","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":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.2606.03371","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03371","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"retail":[1],"agents":[2],"should":[3],"not":[4],"only":[5],"recognize":[6],"what":[7],"a":[8,36,107,143],"customer":[9,44,70,126,187],"is":[10,24],"doing,":[11],"but":[12],"also":[13],"decide":[14],"whether":[15],"and":[16,46,80,91,101,119,147],"how":[17],"to":[18,56,128,158],"assist":[19],"before":[20],"an":[21,50],"explicit":[22],"request":[23],"made.":[25],"We":[26,58,103],"study":[27],"this":[28],"setting":[29],"through":[30],"the":[31,62,161,172],"See--Infer--Intervene":[32],"(SII)":[33],"framework,":[34],"where":[35],"device":[37],"must":[38],"see":[39],"pre-interaction":[40,113],"behavior,":[41],"infer":[42],"latent":[43],"intent,":[45],"act":[47],"by":[48],"selecting":[49],"appropriate":[51],"service":[52],"intervention":[53],"or":[54],"choosing":[55],"wait.":[57],"instantiate":[59],"SII":[60],"with":[61,72,182,199,205],"Proactive":[63],"Intent":[64],"World":[65],"Model":[66],"(PIWM),":[67],"which":[68],"represents":[69],"state":[71,111,127],"AIDA":[73],"(Attention,":[74],"Interest,":[75],"Desire,":[76],"Action)":[77],"purchasing":[78],"phases":[79],"BDI":[81],"(belief,":[82],"desire,":[83],"intention)":[84],"psychological":[85],"fields,":[86],"predicts":[87],"action-conditioned":[88,117],"intent":[89],"transitions,":[90],"selects":[92],"from":[93],"five":[94],"response":[95],"classes:":[96],"Greet,":[97],"Elicit,":[98],"Inform,":[99],"Recommend,":[100],"Hold.":[102],"further":[104],"construct":[105],"GuidanceSalesBench,":[106],"smart-retail":[108],"benchmark":[109],"containing":[110],"manifests,":[112],"videos,":[114,141,198],"candidate":[115],"responses,":[116],"outcomes,":[118],"best-action":[120],"labels.":[121,207],"When":[122],"conditioned":[123],"on":[124,137,194],"ground-truth":[125],"isolate":[129],"action":[130,152,191],"selection,":[131],"PIWM":[132],"achieves":[133],"0.641":[134],"macro":[135,192],"F1":[136,193],"30":[138],"held-out":[139],"target":[140],"outperforming":[142],"zero-shot":[144],"Qwen2.5-VL-7B":[145],"baseline":[146,165],"training":[148],"variants":[149],"without":[150],"balanced":[151,163],"supervision;":[153],"end-to-end":[154],"video-only":[155],"selection":[156],"drops":[157],"0.295,":[159],"below":[160],"5-class":[162],"random":[164],"of":[166],"0.414,":[167],"identifying":[168],"video-to-state":[169],"grounding":[170],"as":[171],"dominant":[173],"deployment-time":[174],"bottleneck.":[175],"A":[176],"preliminary":[177],"staged":[178],"real-store":[179],"pilot":[180],"(recorded":[181],"paid":[183],"participants":[184],"performing":[185],"scripted":[186],"behaviors)":[188],"reaches":[189],"0.579":[190],"20":[195],"fully":[196],"annotated":[197],"10":[200],"additional":[201],"accessible":[202],"videos":[203],"released":[204],"index-level":[206]},"counts_by_year":[],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2026-06-04T00:00:00"}
