{"id":"https://openalex.org/W4410636391","doi":"https://doi.org/10.1145/3701716.3715589","title":"PCL: Prompt-based Continual Learning for User Modeling in Recommender Systems","display_name":"PCL: Prompt-based Continual Learning for User Modeling in Recommender Systems","publication_year":2025,"publication_date":"2025-05-08","ids":{"openalex":"https://openalex.org/W4410636391","doi":"https://doi.org/10.1145/3701716.3715589"},"language":"en","primary_location":{"id":"doi:10.1145/3701716.3715589","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3715589","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715589","source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715589","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038923936","display_name":"Mingdai Yang","orcid":"https://orcid.org/0000-0002-2868-8965"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingdai Yang","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, USA"],"raw_orcid":"https://orcid.org/0000-0002-2868-8965","affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102014086","display_name":"Fan Yang","orcid":"https://orcid.org/0000-0002-0940-4218"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fan Yang","raw_affiliation_strings":["Amazon, Seattle, USA"],"raw_orcid":"https://orcid.org/0000-0002-0940-4218","affiliations":[{"raw_affiliation_string":"Amazon, Seattle, USA","institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I58610484"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010685961","display_name":"Yanhui Guo","orcid":"https://orcid.org/0000-0002-9908-3795"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanhui Guo","raw_affiliation_strings":["Amazon, Seattle, USA"],"raw_orcid":"https://orcid.org/0000-0002-9908-3795","affiliations":[{"raw_affiliation_string":"Amazon, Seattle, USA","institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I58610484"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103973598","display_name":"Shaoyuan Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaoyuan Xu","raw_affiliation_strings":["Amazon, Seattle, USA"],"raw_orcid":"https://orcid.org/0009-0003-0419-1262","affiliations":[{"raw_affiliation_string":"Amazon, Seattle, USA","institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I58610484"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tianchen Zhou","orcid":"https://orcid.org/0009-0008-8772-5624"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianchen Zhou","raw_affiliation_strings":["Amazon, Seattle, USA"],"raw_orcid":"https://orcid.org/0009-0008-8772-5624","affiliations":[{"raw_affiliation_string":"Amazon, Seattle, USA","institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I58610484"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005302236","display_name":"Yetian Chen","orcid":"https://orcid.org/0009-0003-5419-9043"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yetian Chen","raw_affiliation_strings":["Amazon, Seattle, USA"],"raw_orcid":"https://orcid.org/0009-0003-5419-9043","affiliations":[{"raw_affiliation_string":"Amazon, Seattle, USA","institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I58610484"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Simone Shao","orcid":"https://orcid.org/0009-0000-8481-8229"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Simone Shao","raw_affiliation_strings":["Amazon, Seattle, USA"],"raw_orcid":"https://orcid.org/0009-0000-8481-8229","affiliations":[{"raw_affiliation_string":"Amazon, Seattle, USA","institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I58610484"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100409661","display_name":"Jia Liu","orcid":"https://orcid.org/0000-0001-8844-3233"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jia Liu","raw_affiliation_strings":["Amazon &amp; The Ohio State University, Columbus, USA"],"raw_orcid":"https://orcid.org/0000-0001-8844-3233","affiliations":[{"raw_affiliation_string":"Amazon &amp; The Ohio State University, Columbus, USA","institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021319176","display_name":"Yan Gao","orcid":"https://orcid.org/0000-0002-8012-1392"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Gao","raw_affiliation_strings":["Amazon, Seattle, USA"],"raw_orcid":"https://orcid.org/0000-0002-8012-1392","affiliations":[{"raw_affiliation_string":"Amazon, Seattle, USA","institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I58610484"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.8492,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.92056576,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1475","last_page":"1479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9812999963760376,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.9293451309204102},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8306320905685425},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.39045971632003784},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36664798855781555},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36111918091773987}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.9293451309204102},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8306320905685425},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.39045971632003784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36664798855781555},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36111918091773987}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3701716.3715589","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3715589","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715589","source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2502.19628","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2502.19628","pdf_url":"https://arxiv.org/pdf/2502.19628","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3701716.3715589","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701716.3715589","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701716.3715589","source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410636391.pdf","grobid_xml":"https://content.openalex.org/works/W4410636391.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W2803718882","https://openalex.org/W2809290718","https://openalex.org/W2914304175","https://openalex.org/W2966483207","https://openalex.org/W3179436402","https://openalex.org/W4285428788","https://openalex.org/W4379538554","https://openalex.org/W4396757504","https://openalex.org/W4409149660","https://openalex.org/W6601691205"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"User":[0],"modeling":[1],"in":[2,63,118],"large":[3],"e-commerce":[4],"platforms":[5],"aims":[6],"to":[7,65,74,86,155,171],"optimize":[8],"user":[9,31,42,132],"experiences":[10],"by":[11,112],"incorporating":[12],"various":[13],"customer":[14],"activities.":[15],"Traditional":[16],"models":[17,73],"targeting":[18],"a":[19,84,126],"single":[20],"task":[21],"often":[22],"focus":[23],"on":[24,168],"specific":[25],"business":[26],"metrics,":[27],"neglecting":[28],"the":[29,56,92,104,108,113],"comprehensive":[30],"behavior,":[32],"and":[33,61,79,146,157],"thus":[34],"limiting":[35],"their":[36],"effectiveness.":[37,174],"To":[38],"develop":[39],"more":[40],"generalized":[41],"representations,":[43],"some":[44],"existing":[45],"work":[46],"adopts":[47],"Multi-task":[48],"Learning":[49,69,129],"(MTL)":[50],"approaches.":[51],"But":[52],"they":[53],"all":[54],"face":[55],"challenges":[57],"of":[58,94,115],"optimization":[59],"imbalance":[60],"inefficiency":[62],"adapting":[64],"new":[66,76,109],"tasks.":[67],"Continual":[68,128],"(CL),":[70],"which":[71,134],"allows":[72],"learn":[75],"tasks":[77],"incrementally":[78],"independently,":[80],"has":[81],"emerged":[82],"as":[83,138],"solution":[85],"MTL's":[87],"limitations.":[88],"However,":[89],"CL":[90],"faces":[91],"challenge":[93],"catastrophic":[95,148],"forgetting,":[96],"where":[97],"previously":[98],"learned":[99],"knowledge":[100,145],"is":[101,106],"lost":[102],"when":[103],"model":[105],"learning":[107],"task.":[110],"Inspired":[111],"success":[114],"prompt":[116,162],"tuning":[117],"Pretrained":[119],"Language":[120],"Models":[121],"(PLMs),":[122],"we":[123,151],"propose":[124],"PCL,":[125],"Prompt-based":[127],"framework":[130],"for":[131,141],"modeling,":[133],"utilizes":[135],"position-wise":[136],"prompts":[137,154],"external":[139],"memory":[140],"each":[142],"task,":[143],"preserving":[144],"mitigating":[147],"forgetting.":[149],"Additionally,":[150],"design":[152],"contextual":[153],"capture":[156],"leverage":[158],"inter-task":[159],"relationships":[160],"during":[161],"tuning.":[163],"We":[164],"conduct":[165],"extensive":[166],"experiments":[167],"real-world":[169],"datasets":[170],"demonstrate":[172],"PCL's":[173]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
