{"id":"https://openalex.org/W4396758737","doi":"https://doi.org/10.1145/3589334.3645467","title":"ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation","display_name":"ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation","publication_year":2024,"publication_date":"2024-05-08","ids":{"openalex":"https://openalex.org/W4396758737","doi":"https://doi.org/10.1145/3589334.3645467"},"language":"en","primary_location":{"id":"doi:10.1145/3589334.3645467","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645467","pdf_url":null,"source":null,"license":null,"license_id":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036057873","display_name":"Jianghao Lin","orcid":"https://orcid.org/0000-0002-8953-3203"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianghao Lin","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030006503","display_name":"Rong Shan","orcid":"https://orcid.org/0009-0006-8905-1817"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Shan","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008281909","display_name":"Chenxu Zhu","orcid":"https://orcid.org/0000-0001-8320-6845"},"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":"Chenxu 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":"middle","author":{"id":"https://openalex.org/A5074618552","display_name":"Kounianhua Du","orcid":"https://orcid.org/0000-0002-2611-5055"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kounianhua Du","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427434","display_name":"Bo Chen","orcid":"https://orcid.org/0000-0003-3750-2533"},"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":"Bo Chen","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":"middle","author":{"id":"https://openalex.org/A5052977037","display_name":"Shigang Quan","orcid":"https://orcid.org/0009-0000-3761-5242"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shigang Quan","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054330014","display_name":"Ruiming Tang","orcid":"https://orcid.org/0000-0002-9224-2431"},"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":"Ruiming Tang","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":"middle","author":{"id":"https://openalex.org/A5001571390","display_name":"Yong Yu","orcid":"https://orcid.org/0000-0003-0281-8271"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Yu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090720315","display_name":"Weinan Zhang","orcid":"https://orcid.org/0000-0002-0127-2425"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weinan Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5036057873"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":34.3546,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.99764009,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3497","last_page":"3508"},"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/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9975000023841858,"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/computer-science","display_name":"Computer science","score":0.7784466743469238},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.745985209941864},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.6178087592124939},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5782093405723572},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.5741254687309265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4768418073654175},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4531625807285309},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.42835134267807007},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.41408461332321167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7784466743469238},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.745985209941864},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.6178087592124939},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5782093405723572},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.5741254687309265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4768418073654175},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4531625807285309},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.42835134267807007},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.41408461332321167},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589334.3645467","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645467","pdf_url":null,"source":null,"license":null,"license_id":null,"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":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1352182064","display_name":null,"funder_award_id":"62177033, 62322603","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2143570267","https://openalex.org/W2295739661","https://openalex.org/W2548570154","https://openalex.org/W2604662567","https://openalex.org/W2723293840","https://openalex.org/W2783272285","https://openalex.org/W2793768763","https://openalex.org/W2898085636","https://openalex.org/W2911760887","https://openalex.org/W2942947041","https://openalex.org/W2945772520","https://openalex.org/W2962745591","https://openalex.org/W2964052347","https://openalex.org/W2966095354","https://openalex.org/W2981852735","https://openalex.org/W2998207486","https://openalex.org/W3093519337","https://openalex.org/W3098024612","https://openalex.org/W3100199015","https://openalex.org/W3101704389","https://openalex.org/W3104030692","https://openalex.org/W3106252282","https://openalex.org/W3153413682","https://openalex.org/W3155333579","https://openalex.org/W3156055390","https://openalex.org/W3170163874","https://openalex.org/W3175529606","https://openalex.org/W3201915713","https://openalex.org/W3208709726","https://openalex.org/W4213069590","https://openalex.org/W4221159558","https://openalex.org/W4231054948","https://openalex.org/W4288089799","https://openalex.org/W4290944002","https://openalex.org/W4296591867","https://openalex.org/W4321479995","https://openalex.org/W4321485158","https://openalex.org/W4367047145","https://openalex.org/W4385565986","https://openalex.org/W4385568204"],"related_works":["https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680"],"abstract_inverted_index":{"With":[0],"large":[1,35],"language":[2,36],"models":[3,115,246],"(LLMs)":[4],"achieving":[5],"remarkable":[6],"breakthroughs":[7],"in":[8,59,120],"NLP":[9],"domains,":[10,61],"LLM-enhanced":[11],"recommender":[12],"systems":[13],"have":[14,19],"received":[15],"much":[16],"attention":[17],"and":[18,31,40,45,49,98,123,196],"been":[20],"actively":[21],"explored":[22],"currently.":[23],"In":[24],"this":[25],"paper,":[26],"we":[27,47,105,129,164,183],"focus":[28],"on":[29,204,250],"adapting":[30],"empowering":[32],"a":[33,70,107,175,185],"pure":[34],"model":[37],"for":[38,57,117,149,161,179,225],"zero-shot":[39,122,127],"few-shot":[41,124,162,240],"recommendation":[42,60,101,118],"tasks.":[43],"First":[44],"foremost,":[46],"identify":[48],"formulate":[50],"the":[51,80,88,100,138,147,153,192,211,251],"lifelong":[52,226],"sequential":[53,227],"behavior":[54,76,133,158,228],"incomprehension":[55],"problem":[56],"LLMs":[58,63,150],"i.e.,":[62],"fail":[64],"to":[65,136,151,209],"extract":[66,152],"useful":[67],"information":[68],"from":[69,86,156],"textual":[71],"context":[72,83,89],"of":[73,82,91,103,141,190,213],"long":[74],"user":[75,132,157],"sequence,":[77],"even":[78],"if":[79],"length":[81],"is":[84],"far":[85],"reaching":[87],"limitation":[90],"LLMs.":[92],"To":[93,230],"address":[94],"such":[95],"an":[96],"issue":[97],"improve":[99,137],"performance":[102],"LLMs,":[104],"propose":[106],"novel":[108],"framework,":[109],"namely":[110],"Retrieval":[111],"enhanced":[112],"Large":[113],"Language":[114],"(ReLLa)":[116],"tasks":[119],"both":[121,191],"settings.":[125],"For":[126],"recommendation,":[128,163],"perform":[130],"semantic":[131],"retrieval":[134],"(SUBR)":[135],"data":[139,176,194],"quality":[140],"testing":[142],"samples,":[143,239],"which":[144],"greatly":[145],"reduces":[146],"difficulty":[148],"essential":[154],"knowledge":[155],"sequences.":[159],"As":[160],"further":[165],"design":[166],"retrieval-enhanced":[167,198],"instruction":[168],"tuning":[169],"(ReiT)":[170],"by":[171],"adopting":[172],"SUBR":[173],"as":[174,220,222],"augmentation":[177],"technique":[178],"training":[180,187,238,253],"samples.":[181],"Specifically,":[182],"develop":[184],"mixed":[186],"dataset":[188],"consisting":[189],"original":[193],"samples":[195],"their":[197],"counterparts.":[199],"We":[200],"conduct":[201],"extensive":[202],"experiments":[203],"three":[205],"real-world":[206],"public":[207],"datasets":[208],"demonstrate":[210],"superiority":[212],"ReLLa":[214,241],"compared":[215],"with":[216,233],"existing":[217],"baseline":[218],"models,":[219],"well":[221],"its":[223],"capability":[224],"comprehension.":[229],"be":[231],"highlighted,":[232],"only":[234],"less":[235],"than":[236],"10%":[237],"can":[242],"outperform":[243],"traditional":[244],"CTR":[245],"that":[247],"are":[248],"trained":[249],"entire":[252],"set":[254],"(e.g.,":[255],"DCNv2,":[256],"DIN,":[257],"SIM).":[258]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":30},{"year":2024,"cited_by_count":12}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
