{"id":"https://openalex.org/W7117548371","doi":"https://doi.org/10.1145/3770854.3780214","title":"TAMEing Long Contexts in Personalization: Towards Training-Free and State-Aware MLLM Personalized Assistant","display_name":"TAMEing Long Contexts in Personalization: Towards Training-Free and State-Aware MLLM Personalized Assistant","publication_year":2025,"publication_date":"2025-12-25","ids":{"openalex":"https://openalex.org/W7117548371","doi":"https://doi.org/10.1145/3770854.3780214"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.21616","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.21616","pdf_url":"https://arxiv.org/pdf/2512.21616","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"article","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.21616","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033820450","display_name":"Rongpei Hong","orcid":"https://orcid.org/0009-0007-4977-1657"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hong, Rongpei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121538229","display_name":"Jian Lang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lang, Jian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121565198","display_name":"Ting Zhong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhong, Ting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121577062","display_name":"Yong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5121565671","display_name":"Fan Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Fan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5033820450"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.80500311,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T10028","display_name":"Topic Modeling","score":0.5020999908447266,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.5020999908447266,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.18569999933242798,"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/T12031","display_name":"Speech and dialogue systems","score":0.041200000792741776,"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/personalization","display_name":"Personalization","score":0.896399974822998},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.578000009059906},{"id":"https://openalex.org/keywords/personalized-learning","display_name":"Personalized learning","score":0.4733999967575073},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.46219998598098755},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.44929999113082886},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4383000135421753},{"id":"https://openalex.org/keywords/ideal","display_name":"Ideal (ethics)","score":0.3723999857902527}],"concepts":[{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.896399974822998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6833000183105469},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.578000009059906},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4997999966144562},{"id":"https://openalex.org/C142039133","wikidata":"https://www.wikidata.org/wiki/Q3620943","display_name":"Personalized learning","level":5,"score":0.4733999967575073},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.46219998598098755},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4383000135421753},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.3723999857902527},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3499000072479248},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.3481000065803528},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.32659998536109924},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C2778726489","wikidata":"https://www.wikidata.org/wiki/Q39266","display_name":"Puppy","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:arXiv.org:2512.21616","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.21616","pdf_url":"https://arxiv.org/pdf/2512.21616","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2512.21616","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.21616","pdf_url":"https://arxiv.org/pdf/2512.21616","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"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],"Large":[1],"Language":[2],"Model":[3],"(MLLM)":[4],"Personalization":[5,95],"is":[6,63],"a":[7,121,128,153,160],"critical":[8],"research":[9],"problem":[10],"that":[11,116,200],"facilitates":[12],"personalized":[13,22,41,60,108,114,150],"dialogues":[14,69],"with":[15,70,138],"MLLMs":[16,103,137],"targeting":[17],"specific":[18],"entities":[19],"(known":[20],"as":[21],"concepts).":[23],"However,":[24],"existing":[25],"methods":[26],"and":[27,36,72,110,131,145,208],"benchmarks":[28],"focus":[29],"on":[30,197],"the":[31,40,52,91,100,143,175,180,185,203],"simple,":[32],"context-agnostic":[33],"visual":[34],"identification":[35],"textual":[37],"replacement":[38],"of":[39,65,102,107,148],"concept":[42,151],"(e.g.,":[43],"\"A":[44],"yellow":[45],"puppy\"":[46],"->":[47],"\"Your":[48],"puppy":[49],"Mochi\"),":[50],"overlooking":[51],"ability":[53],"to":[54,141,173,184],"support":[55],"long-context":[56,68,213],"conversations.":[57],"An":[58],"ideal":[59],"MLLM":[61,94],"assistant":[62],"capable":[64],"engaging":[66],"in":[67,104,152,212],"humans":[71],"continually":[73],"improving":[74],"its":[75],"experience":[76],"quality":[77],"by":[78],"learning":[79],"from":[80,179],"past":[81],"dialogue":[82],"histories.":[83],"To":[84],"bridge":[85],"this":[86],"gap,":[87],"we":[88,126],"propose":[89],"LCMP,":[90,125],"first":[92],"Long-Context":[93],"evaluation":[96],"benchmark.":[97],"LCMP":[98,198],"assesses":[99],"capability":[101],"perceiving":[105],"variations":[106,147],"concepts":[109],"generating":[111],"contextually":[112,176],"appropriate":[113],"responses":[115],"reflect":[117],"these":[118],"variations.":[119],"As":[120],"strong":[122],"baseline":[123],"for":[124,191],"introduce":[127],"novel":[129],"training-free":[130,162],"state-aware":[132],"framework":[133],"TAME.":[134],"TAME":[135,158,201],"endows":[136],"double":[139],"memories":[140],"manage":[142],"temporal":[144],"persistent":[146],"each":[149],"differentiated":[154],"manner.":[155],"In":[156],"addition,":[157],"incorporates":[159],"new":[161],"Retrieve-then-Align":[163],"Augmented":[164],"Generation":[165],"(RA2G)":[166],"paradigm.":[167],"RA2G":[168],"introduces":[169],"an":[170],"alignment":[171],"step":[172],"extract":[174],"fitted":[177],"information":[178],"multi-memory":[181],"retrieved":[182],"knowledge":[183],"current":[186],"questions,":[187],"enabling":[188],"better":[189],"interactions":[190],"complex":[192],"real-world":[193],"user":[194],"queries.":[195],"Experiments":[196],"demonstrate":[199],"achieves":[202],"best":[204],"performance,":[205],"showcasing":[206],"remarkable":[207],"evolving":[209],"interaction":[210],"experiences":[211],"scenarios.":[214]},"counts_by_year":[],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-12-30T00:00:00"}
