{"id":"https://openalex.org/W4396723563","doi":"https://doi.org/10.1145/3589334.3645633","title":"PMG : Personalized Multimodal Generation with Large Language Models","display_name":"PMG : Personalized Multimodal Generation with Large Language Models","publication_year":2024,"publication_date":"2024-05-08","ids":{"openalex":"https://openalex.org/W4396723563","doi":"https://doi.org/10.1145/3589334.3645633"},"language":"en","primary_location":{"id":"doi:10.1145/3589334.3645633","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589334.3645633","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3589334.3645633","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057093904","display_name":"Xiaoteng Shen","orcid":"https://orcid.org/0009-0002-9559-3293"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoteng Shen","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422092","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0002-8132-6250"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["www.ruizhang.info, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"www.ruizhang.info, Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101594431","display_name":"Xiaoyan Zhao","orcid":"https://orcid.org/0000-0001-6001-1260"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Zhao","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048669373","display_name":"Jieming Zhu","orcid":"https://orcid.org/0000-0002-5666-8320"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jieming Zhu","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101600503","display_name":"Xi Xiao","orcid":"https://orcid.org/0000-0003-1521-9542"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Xiao","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5057093904"],"corresponding_institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":9.0401,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.98192494,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3833","last_page":"3843"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9984999895095825,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8770211338996887},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8050938844680786},{"id":"https://openalex.org/keywords/natural-language-generation","display_name":"Natural language generation","score":0.7416877150535583},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.6698271036148071},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6552003026008606},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4910554885864258},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4358759820461273},{"id":"https://openalex.org/keywords/text-generation","display_name":"Text generation","score":0.42585518956184387},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.396408349275589},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3099673390388489},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.2599595785140991},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.24245095252990723}],"concepts":[{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.8770211338996887},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8050938844680786},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.7416877150535583},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.6698271036148071},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6552003026008606},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4910554885864258},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4358759820461273},{"id":"https://openalex.org/C2985684807","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Text generation","level":2,"score":0.42585518956184387},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.396408349275589},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3099673390388489},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2599595785140991},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.24245095252990723},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589334.3645633","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589334.3645633","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3589334.3645633","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589334.3645633","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.4000000059604645,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2133665775","https://openalex.org/W2946617802","https://openalex.org/W2962785568","https://openalex.org/W2982108874","https://openalex.org/W4212774754","https://openalex.org/W4283324387","https://openalex.org/W4296591867","https://openalex.org/W4312238419","https://openalex.org/W4312933868","https://openalex.org/W4367359628","https://openalex.org/W4372266552","https://openalex.org/W4386072096","https://openalex.org/W4386114032"],"related_works":["https://openalex.org/W2066972210","https://openalex.org/W4287812620","https://openalex.org/W1763968285","https://openalex.org/W3019906500","https://openalex.org/W4285816270","https://openalex.org/W2171759076","https://openalex.org/W2573463306","https://openalex.org/W1816112200","https://openalex.org/W3196937884","https://openalex.org/W4385570684"],"abstract_inverted_index":{"The":[0,70],"emergence":[1],"of":[2,11,143,156,173,210,216],"large":[3],"language":[4,96],"models":[5],"(LLMs)":[6],"has":[7,36,184,198],"revolutionized":[8],"the":[9,23,46,138,154,166,174,181,214],"capabilities":[10],"text":[12],"comprehension":[13],"and":[14,25,58,101,132,146,158,176],"generation.":[15,217],"Multi-modal":[16],"generation":[17,52],"attracts":[18],"great":[19],"attention":[20],"from":[21],"both":[22],"industry":[24],"academia,":[26],"but":[27],"there":[28],"is":[29],"little":[30],"work":[31],"on":[32,67,202],"personalized":[33,50,125],"generation,":[34],"which":[35],"important":[37],"applications":[38,57],"such":[39,115],"as":[40,116,162],"recommender":[41,86],"systems.":[42],"This":[43],"paper":[44],"proposes":[45],"first":[47,79],"method":[48,194],"for":[49,77,204],"multimodal":[51,118],"using":[53],"LLMs,":[54],"showcases":[55],"its":[56,60],"validates":[59],"performance":[61],"via":[62],"an":[63],"extensive":[64],"experimental":[65],"study":[66],"two":[68],"datasets.":[69],"proposed":[71],"method,":[72],"Personalized":[73],"Multimodal":[74],"Generation":[75],"(PMG":[76],"short)":[78],"converts":[80],"user":[81,103,107,129,151],"behaviors":[82],"(e.g.,":[83],"clicks":[84],"in":[85,208],"systems":[87],"or":[88,120],"conversations":[89],"with":[90],"a":[91,113,117,141,170,185,192,199],"virtual":[92],"assistant)":[93],"into":[94,112],"natural":[95],"to":[97,123,136,149,164,191,206],"facilitate":[98],"LLM":[99,119,139],"understanding":[100],"extract":[102],"preference":[104,177],"descriptions.":[105],"Such":[106],"preferences":[108,130],"are":[109,160],"then":[110],"fed":[111],"generator,":[114],"diffusion":[121],"model,":[122],"produce":[124],"content.":[126],"To":[127],"capture":[128],"comprehensively":[131],"accurately,":[133],"we":[134],"propose":[135],"let":[137],"output":[140],"combination":[142,155],"explicit":[144],"keywords":[145,157],"implicit":[147],"embeddings":[148,159],"represent":[150],"preferences.":[152],"Then":[153],"used":[161],"prompts":[163],"condition":[165],"generator.":[167],"We":[168],"optimize":[169],"weighted":[171],"sum":[172],"accuracy":[175,215],"scores":[178],"so":[179],"that":[180],"generated":[182],"content":[183],"good":[186],"balance":[187],"between":[188],"them.":[189],"Compared":[190],"baseline":[193],"without":[195],"personalization,":[196],"PMG":[197],"significant":[200],"improvement":[201],"personalization":[203],"up":[205],"8%":[207],"terms":[209],"LPIPS":[211],"while":[212],"retaining":[213]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":6}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}