{"id":"https://openalex.org/W4403220680","doi":"https://doi.org/10.1145/3640457.3688135","title":"LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding","display_name":"LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding","publication_year":2024,"publication_date":"2024-10-08","ids":{"openalex":"https://openalex.org/W4403220680","doi":"https://doi.org/10.1145/3640457.3688135"},"language":"en","primary_location":{"id":"doi:10.1145/3640457.3688135","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3640457.3688135","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688135","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"18th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688135","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhizhong Wan","orcid":"https://orcid.org/0009-0005-8624-9249"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhizhong Wan","raw_affiliation_strings":["Waimai, Meituan, China"],"raw_orcid":"https://orcid.org/0009-0005-8624-9249","affiliations":[{"raw_affiliation_string":"Waimai, Meituan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092867473","display_name":"Bin Yin","orcid":"https://orcid.org/0009-0007-3228-2670"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bin Yin","raw_affiliation_strings":["Waimai, Meituan, China"],"raw_orcid":"https://orcid.org/0009-0007-3228-2670","affiliations":[{"raw_affiliation_string":"Waimai, Meituan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101637206","display_name":"Junjie Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junjie Xie","raw_affiliation_strings":["Waimai, Meituan, China"],"raw_orcid":"https://orcid.org/0009-0009-2793-0092","affiliations":[{"raw_affiliation_string":"Waimai, Meituan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066285824","display_name":"Fei Jiang","orcid":"https://orcid.org/0000-0002-7019-140X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fei Jiang","raw_affiliation_strings":["Waimai, Meituan, China"],"raw_orcid":"https://orcid.org/0000-0002-7019-140X","affiliations":[{"raw_affiliation_string":"Waimai, Meituan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013394366","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0003-2834-8765"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["Waimai, Meituan, China"],"raw_orcid":"https://orcid.org/0000-0003-2834-8765","affiliations":[{"raw_affiliation_string":"Waimai, Meituan, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100364629","display_name":"Wei Lin","orcid":"https://orcid.org/0000-0003-2851-820X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Lin","raw_affiliation_strings":["Waimai, Meituan, China"],"raw_orcid":"https://orcid.org/0000-0003-2851-820X","affiliations":[{"raw_affiliation_string":"Waimai, Meituan, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.298,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.85736006,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"23","last_page":"32"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9857000112533569,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8492901921272278},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6305407285690308},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6001606583595276},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5511802434921265},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.49706438183784485},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4729100167751312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.470316082239151},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4521043002605438},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4467129707336426},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4286189675331116},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.32998204231262207},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.07688504457473755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8492901921272278},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6305407285690308},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6001606583595276},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5511802434921265},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.49706438183784485},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4729100167751312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.470316082239151},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4521043002605438},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4467129707336426},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4286189675331116},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32998204231262207},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07688504457473755},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3640457.3688135","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3640457.3688135","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688135","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"18th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2408.11523","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.11523","pdf_url":"https://arxiv.org/pdf/2408.11523","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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:10.1145/3640457.3688135","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3640457.3688135","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3640457.3688135","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"18th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4403220680.pdf"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2475334473","https://openalex.org/W2793768763","https://openalex.org/W2809290718","https://openalex.org/W2946044191","https://openalex.org/W2981852735","https://openalex.org/W3011574394","https://openalex.org/W3087931390","https://openalex.org/W3104030692","https://openalex.org/W3104789011","https://openalex.org/W3169113923","https://openalex.org/W4224308101","https://openalex.org/W4285294723","https://openalex.org/W4288089799","https://openalex.org/W4296591867","https://openalex.org/W4386081001","https://openalex.org/W4386728881","https://openalex.org/W4386728933","https://openalex.org/W4386729835","https://openalex.org/W4392367398","https://openalex.org/W6810081322"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W3125580266","https://openalex.org/W4288390103","https://openalex.org/W4317039510","https://openalex.org/W4238861846"],"abstract_inverted_index":{"Click-Through":[0],"Rate":[1],"(CTR)":[2],"prediction":[3],"is":[4,59,117,140,158,174],"crucial":[5],"for":[6,15,55,85,185],"Recommendation":[7],"System(RS),":[8],"aiming":[9],"to":[10,39,97,128,195],"provide":[11],"personalized":[12],"recommendation":[13,57,114,147,204],"services":[14],"users":[16],"in":[17,49,62,92,198],"many":[18],"aspects":[19],"such":[20],"as":[21],"food":[22],"delivery,":[23],"e-commerce":[24],"and":[25,121],"so":[26],"on.":[27],"However,":[28],"traditional":[29],"RS":[30,93,123],"relies":[31],"on":[32,143,163],"collaborative":[33,196],"signals,":[34],"which":[35],"lacks":[36],"semantic":[37,86],"understanding":[38],"real-time":[40,89,101,130],"scenes.":[41],"We":[42],"also":[43],"noticed":[44],"that":[45],"a":[46,138,177],"major":[47],"challenge":[48],"utilizing":[50,88],"Large":[51,76],"Language":[52,77],"Models":[53],"(LLMs)":[54],"practical":[56],"purposes":[58],"their":[60],"efficiency":[61,108],"dealing":[63],"with":[64,149],"long":[65],"text":[66,103,178],"input.":[67],"To":[68],"break":[69],"through":[70],"the":[71,99,107,150,156,201],"problems":[72],"above,":[73],"we":[74],"propose":[75],"Model":[78],"Aided":[79],"Real-time":[80],"Scene":[81],"Recommendation(LARR),":[82],"adopt":[83],"LLMs":[84],"understanding,":[87],"scene":[90,102,131,187],"information":[91,132],"without":[94],"requiring":[95],"LLM":[96,120,139,157,173],"process":[98],"entire":[100],"directly,":[104],"thereby":[105],"enhancing":[106,200],"of":[109,152,166,203],"LLM-based":[110],"CTR":[111],"modeling.":[112],"Specifically,":[113],"domain-specific":[115],"knowledge":[116],"injected":[118],"into":[119,176],"then":[122],"employs":[124],"an":[125,192],"aggregation":[126],"encoder":[127],"build":[129],"from":[133,146],"separate":[134,183],"LLM\u2019s":[135,182],"outputs.":[136],"Firstly,":[137],"continual":[141],"pretrained":[142],"corpus":[144],"built":[145],"data":[148],"aid":[151],"special":[153],"tokens.":[154],"Subsequently,":[155],"fine-tuned":[159],"via":[160],"contrastive":[161],"learning":[162],"three":[164],"kinds":[165],"sample":[167],"construction":[168],"strategies.":[169],"Through":[170],"this":[171],"step,":[172],"transformed":[175],"embedding":[179],"model.":[180,205],"Finally,":[181],"outputs":[184],"different":[186],"features":[188],"are":[189],"aggregated":[190],"by":[191],"encoder,":[193],"aligning":[194],"signals":[197],"RS,":[199],"performance":[202]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}
