{"id":"https://openalex.org/W4412376952","doi":"https://doi.org/10.1145/3726302.3730059","title":"Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Models","display_name":"Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Models","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412376952","doi":"https://doi.org/10.1145/3726302.3730059"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3730059","doi":"https://doi.org/10.1145/3726302.3730059","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730059","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730059","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730059","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043861652","display_name":"Yuhao Wang","orcid":"https://orcid.org/0000-0002-6051-8659","observed_orcids":["https://orcid.org/0000-0002-6051-8659"]},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuhao Wang","raw_affiliation_strings":["City University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-6051-8659","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024752665","display_name":"Junwei Pan","orcid":"https://orcid.org/0009-0003-2697-7012","observed_orcids":["https://orcid.org/0009-0003-2697-7012"]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junwei Pan","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0003-2697-7012","affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094239331","display_name":"Pengyue Jia","orcid":"https://orcid.org/0000-0003-4712-3676","observed_orcids":["https://orcid.org/0000-0003-4712-3676"]},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Pengyue Jia","raw_affiliation_strings":["City University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-4712-3676","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059573675","display_name":"Wanyu Wang","orcid":"https://orcid.org/0000-0001-5976-0707","observed_orcids":["https://orcid.org/0000-0001-5976-0707"]},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wanyu Wang","raw_affiliation_strings":["City University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-5976-0707","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Maolin Wang","orcid":"https://orcid.org/0000-0002-0073-0172","observed_orcids":["https://orcid.org/0000-0002-0073-0172"]},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Maolin Wang","raw_affiliation_strings":["City University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0002-0073-0172","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100584528","display_name":"Zhixiang Feng","orcid":"https://orcid.org/0009-0005-1519-0227","observed_orcids":["https://orcid.org/0009-0005-1519-0227"]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixiang Feng","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0005-1519-0227","affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070298048","display_name":"X. Li","orcid":"https://orcid.org/0009-0000-7547-8525","observed_orcids":["https://orcid.org/0009-0000-7547-8525"]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaotian Li","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0000-7547-8525","affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037387576","display_name":"Jie Jiang","orcid":"https://orcid.org/0000-0001-9658-5127","observed_orcids":["https://orcid.org/0000-0001-9658-5127"]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Jiang","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-9658-5127","affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100645854","display_name":"Xiangyu Zhao","orcid":"https://orcid.org/0000-0003-2926-4416","observed_orcids":["https://orcid.org/0000-0003-2926-4416","https://orcid.org/0000-0003-2035-6058"]},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiangyu Zhao","raw_affiliation_strings":["City University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-2926-4416","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.4953,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.98493321,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1455","last_page":"1465"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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":1.0,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.0,"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":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sequential-recommendation","display_name":"sequential recommendation","score":0.9990000128746033},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9980000257492065},{"id":"https://openalex.org/keywords/cold-start","display_name":"cold start","score":0.8259999752044678},{"id":"https://openalex.org/keywords/catastrophic-forgetting","display_name":"catastrophic forgetting","score":0.7730000019073486},{"id":"https://openalex.org/keywords/disentangled-representations","display_name":"disentangled representations","score":0.7070000171661377},{"id":"https://openalex.org/keywords/multi-kernel-maximum-mean-discrepancy","display_name":"multi-kernel maximum mean discrepancy","score":0.8600000143051147},{"id":"https://openalex.org/keywords/inference-latency","display_name":"inference latency","score":0.5090000033378601}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.758507490158081},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.48997417092323303},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4000636339187622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34872183203697205}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3726302.3730059","doi":"https://doi.org/10.1145/3726302.3730059","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730059","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730059","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2412.04107","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.04107","pdf_url":"https://arxiv.org/pdf/2412.04107","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,"listed_in":[],"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"},{"id":"doi:10.48550/arxiv.2412.04107","doi":"https://doi.org/10.48550/arxiv.2412.04107","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2412.04107","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,"listed_in":[],"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:10.1145/3726302.3730059","doi":"https://doi.org/10.1145/3726302.3730059","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730059","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730059","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Reduced inequalities","score":0.75,"id":"https://metadata.un.org/sdg/10"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412376952.pdf","grobid_xml":"https://content.openalex.org/works/W4412376952.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1985514943","https://openalex.org/W2074694452","https://openalex.org/W2076618162","https://openalex.org/W2723293840","https://openalex.org/W2741249238","https://openalex.org/W2783272285","https://openalex.org/W2788295351","https://openalex.org/W2799544270","https://openalex.org/W2962745591","https://openalex.org/W2963367478","https://openalex.org/W2963655167","https://openalex.org/W2964258748","https://openalex.org/W2969960436","https://openalex.org/W2971196067","https://openalex.org/W2982108874","https://openalex.org/W2984100107","https://openalex.org/W3034503922","https://openalex.org/W3093519337","https://openalex.org/W3096591391","https://openalex.org/W3101183984","https://openalex.org/W4306317051","https://openalex.org/W4306317444","https://openalex.org/W4319653664","https://openalex.org/W4367047350","https://openalex.org/W4384641542","https://openalex.org/W4384648324","https://openalex.org/W4385562613","https://openalex.org/W4386728933","https://openalex.org/W4386729350","https://openalex.org/W4387846171","https://openalex.org/W4389893572","https://openalex.org/W4392384596","https://openalex.org/W4392489983","https://openalex.org/W4393159871","https://openalex.org/W4394007749","https://openalex.org/W4400909953","https://openalex.org/W4400910477","https://openalex.org/W4401857429","https://openalex.org/W4403220893","https://openalex.org/W4403221552","https://openalex.org/W4403577824","https://openalex.org/W4403582517","https://openalex.org/W6600103761","https://openalex.org/W6600238479","https://openalex.org/W6600339963"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Sequential":[0],"Recommendation":[1],"(SR)":[2],"aims":[3],"to":[4,13,88,105],"leverage":[5],"the":[6,19,34,42,100,152],"sequential":[7],"patterns":[8],"in":[9,30,141],"users'":[10],"historical":[11],"interactions":[12],"accurately":[14],"track":[15],"their":[16,50],"preferences.":[17],"However,":[18],"primary":[20],"reliance":[21],"of":[22,45,67,154],"existing":[23],"SR":[24,90,101,163],"methods":[25],"on":[26,147],"collaborative":[27,107],"data":[28],"results":[29,146],"challenges":[31],"such":[32,60],"as":[33,61],"cold-start":[35],"problem":[36],"and":[37,71,84,102,108,133,159,172],"sub-optimal":[38],"performance.":[39],"Concurrently,":[40],"despite":[41],"proven":[43],"effectiveness":[44],"large":[46],"language":[47],"models":[48,91,104],"(LLMs),":[49],"integration":[51],"into":[52],"commercial":[53],"recommender":[54],"systems":[55],"is":[56,139],"impeded":[57],"by":[58],"issues":[59],"high":[62],"inference":[63],"latency,":[64],"incomplete":[65],"capture":[66],"all":[68],"distribution":[69],"statistics,":[70],"catastrophic":[72],"forgetting.":[73],"To":[74],"address":[75],"these":[76],"issues,":[77],"we":[78,96,112],"introduce":[79],"a":[80,114,128,142],"novel":[81],"Pre-train,":[82],"Align,":[83],"Disentangle":[85],"(PAD)":[86],"framework":[87],"enhance":[89],"with":[92,124,136,161],"LLMs.":[93],"In":[94],"particular,":[95],"initially":[97],"pre-train":[98],"both":[99],"LLM":[103],"obtain":[106],"textual":[109],"embeddings.":[110],"Subsequently,":[111],"propose":[113],"characteristic":[115],"recommendation-anchored":[116],"alignment":[117],"loss":[118],"using":[119],"multi-kernel":[120],"maximum":[121],"mean":[122],"discrepancy":[123],"Gaussian":[125],"kernels.":[126],"Lastly,":[127],"triple-experts":[129],"architecture,":[130],"comprising":[131],"aligned":[132],"modality-specific":[134],"experts":[135],"disentangled":[137],"embeddings,":[138],"fine-tuned":[140],"frequency-aware":[143],"manner.":[144],"Experimental":[145],"three":[148],"public":[149],"datasets":[150,173],"validate":[151],"efficacy":[153],"PAD,":[155],"indicating":[156],"substantial":[157],"enhancements":[158],"compatibility":[160],"various":[162],"backbone":[164],"models,":[165],"particularly":[166],"for":[167,176],"cold":[168],"items.":[169],"The":[170],"code":[171],"are":[174],"accessible":[175],"reproduction:":[177],"https://github.com/Applied-Machine-Learning-Lab/PAD.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":4}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}