{"id":"https://openalex.org/W7162565688","doi":"https://doi.org/10.48550/arxiv.2605.26256","title":"Personalizing Embodied Multimodal Large Language Model Agents over Long-term User Interactions","display_name":"Personalizing Embodied Multimodal Large Language Model Agents over Long-term User Interactions","publication_year":2026,"publication_date":"2026-05-25","ids":{"openalex":"https://openalex.org/W7162565688","doi":"https://doi.org/10.48550/arxiv.2605.26256"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.26256","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26256","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.26256","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100673343","display_name":"J. Lee","orcid":"https://orcid.org/0000-0002-5351-7201"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Jeongeun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137158262","display_name":"Chanyoung Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Chanyoung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137143565","display_name":"Dongha Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Dongha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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":0.9211999773979187,"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":0.9211999773979187,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.010300000198185444,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.007600000128149986,"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/embodied-cognition","display_name":"Embodied cognition","score":0.8804000020027161},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7121999859809875},{"id":"https://openalex.org/keywords/embodied-agent","display_name":"Embodied agent","score":0.5273000001907349},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5148000121116638},{"id":"https://openalex.org/keywords/language-understanding","display_name":"Language understanding","score":0.43470001220703125},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4284999966621399},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42489999532699585},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4226999878883362},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.3817000091075897}],"concepts":[{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.8804000020027161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8172000050544739},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7121999859809875},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5993000268936157},{"id":"https://openalex.org/C103683099","wikidata":"https://www.wikidata.org/wiki/Q5370102","display_name":"Embodied agent","level":3,"score":0.5273000001907349},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5148000121116638},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.43470001220703125},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42489999532699585},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4226999878883362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3903000056743622},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3817000091075897},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3594000041484833},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3521000146865845},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.3328999876976013},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C135641252","wikidata":"https://www.wikidata.org/wiki/Q738567","display_name":"Multimodal interaction","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C190954187","wikidata":"https://www.wikidata.org/wiki/Q5270587","display_name":"Dialog system","level":3,"score":0.28780001401901245},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.2768000066280365},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.25119999051094055},{"id":"https://openalex.org/C88576662","wikidata":"https://www.wikidata.org/wiki/Q18646","display_name":"Episodic memory","level":3,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.26256","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26256","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.26256","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26256","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"large":[1],"language":[2],"model":[3],"(MLLM)-based":[4],"embodied":[5,66,95,103],"agents":[6,46,67,166],"have":[7],"shown":[8],"strong":[9],"potential":[10],"for":[11,64,85,94],"solving":[12],"complex":[13],"tasks":[14],"in":[15,135,180],"physical":[16],"environments.":[17],"However,":[18],"personalized":[19,49,65,86],"assistance":[20],"requires":[21],"more":[22,150],"than":[23],"following":[24],"generic":[25],"instruction":[26],"or":[27,177],"recognizing":[28],"object":[29],"categories.":[30],"In":[31,54],"real-world":[32],"scenarios,":[33],"the":[34,111,131,141,165],"intended":[35],"target":[36],"is":[37],"often":[38],"specified":[39],"only":[40],"implicitly":[41],"through":[42],"prior":[43,74,157],"interactions,":[44,173],"requiring":[45],"to":[47,109,129,169],"leverage":[48],"context":[50,87,182],"accumulated":[51,155],"over":[52,68,156,183],"time.":[53,184],"this":[55],"work,":[56],"we":[57],"propose":[58],"POLAR,":[59],"a":[60,77],"multiomodal":[61],"memory-augmented":[62],"framework":[63],"long-term":[69,136],"user":[70],"interactions.":[71,158],"POLAR":[72,105,120],"organizes":[73],"interactions":[75],"into":[76],"multimodal":[78],"knowledge":[79],"graph":[80],"that":[81,140],"captures":[82],"semantic":[83],"memory":[84,93,134,143],"and":[88,91,114,125],"visual":[89],"concepts,":[90],"episodic":[92],"experiences":[96],"such":[97],"as":[98],"agent":[99],"trajectories.":[100],"To":[101],"execute":[102],"tasks,":[104],"retrieves":[106],"relevant":[107],"memories":[108],"interpret":[110],"current":[112],"request":[113],"guide":[115],"task":[116],"execution.":[117],"We":[118],"evaluate":[119],"across":[121,171],"multiple":[122,172],"MLLM":[123],"backbones":[124],"diverse":[126],"evaluation":[127],"scenarios":[128],"study":[130],"role":[132],"of":[133,153],"personalization.":[137],"Results":[138],"show":[139],"proposed":[142],"mechanism":[144],"consistently":[145],"improves":[146],"performance":[147],"by":[148],"enabling":[149],"effective":[151],"use":[152],"information":[154],"The":[159],"gains":[160],"are":[161,167],"especially":[162],"pronounced":[163],"when":[164],"required":[168],"reason":[170],"perform":[174],"multi-hop":[175],"inference,":[176],"tracking":[178],"updates":[179],"user-specific":[181]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-28T00:00:00"}
