{"id":"https://openalex.org/W7167890006","doi":"https://doi.org/10.1145/3805712.3809736","title":"Countering Interest Over-Smoothing: Distilling Latent Factors via Diffusion for Multi-Interest Retrieval","display_name":"Countering Interest Over-Smoothing: Distilling Latent Factors via Diffusion for Multi-Interest Retrieval","publication_year":2026,"publication_date":"2026-07-10","ids":{"openalex":"https://openalex.org/W7167890006","doi":"https://doi.org/10.1145/3805712.3809736"},"language":null,"primary_location":{"id":"doi:10.1145/3805712.3809736","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805712.3809736","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 49th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805712.3809736","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139721533","display_name":"Yankun Le","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yankun Le","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China"],"raw_orcid":"https://orcid.org/0009-0008-2228-3474","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074356086","display_name":"Fu Zhang","orcid":"https://orcid.org/0000-0002-3880-8086"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fu Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China"],"raw_orcid":"https://orcid.org/0000-0002-3880-8086","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140445873","display_name":"Haoran Li","orcid":"https://orcid.org/0009-0001-2095-1060"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haoran Li","raw_affiliation_strings":["Xiaohongshu Inc., Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0001-2095-1060","affiliations":[{"raw_affiliation_string":"Xiaohongshu Inc., Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140390098","display_name":"Baoyuan Ou","orcid":"https://orcid.org/0009-0007-5709-5986"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baoyuan Ou","raw_affiliation_strings":["Xiaohongshu Inc., Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0007-5709-5986","affiliations":[{"raw_affiliation_string":"Xiaohongshu Inc., Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140386310","display_name":"Yingjie Qin","orcid":"https://orcid.org/0009-0005-5078-2201"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yingjie Qin","raw_affiliation_strings":["Xiaohongshu Inc., Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0005-5078-2201","affiliations":[{"raw_affiliation_string":"Xiaohongshu Inc., Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139715843","display_name":"Zhixuan Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixuan Yang","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China"],"raw_orcid":"https://orcid.org/0009-0005-3583-4720","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5140446004","display_name":"Ruilong Su","orcid":"https://orcid.org/0009-0003-6695-4536"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruilong Su","raw_affiliation_strings":["Xiaohongshu Inc., Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0003-6695-4536","affiliations":[{"raw_affiliation_string":"Xiaohongshu Inc., Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.9387827,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"881","last_page":"890"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.8992999792098999,"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":0.8992999792098999,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.023900000378489494,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.008100000210106373,"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/matching","display_name":"Matching (statistics)","score":0.6220999956130981},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5975000262260437},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5662000179290771},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.45730000734329224},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.4106999933719635},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.3474999964237213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7529000043869019},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6220999956130981},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5975000262260437},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5662000179290771},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.45730000734329224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44830000400543213},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.4106999933719635},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4004000127315521},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37950000166893005},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3447999954223633},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C2778956030","wikidata":"https://www.wikidata.org/wiki/Q5142477","display_name":"Cold start (automotive)","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C68710425","wikidata":"https://www.wikidata.org/wiki/Q5275442","display_name":"Diffusion process","level":3,"score":0.27639999985694885},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805712.3809736","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805712.3809736","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 49th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805712.3809736","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805712.3809736","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 49th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2110953678","https://openalex.org/W2512971201","https://openalex.org/W2982902390","https://openalex.org/W2987999026","https://openalex.org/W3172874940","https://openalex.org/W4285818639","https://openalex.org/W4306317061","https://openalex.org/W4384644330","https://openalex.org/W4386729443","https://openalex.org/W4387846486","https://openalex.org/W4390412407","https://openalex.org/W4390534603","https://openalex.org/W4393147800","https://openalex.org/W4400527101","https://openalex.org/W4401863487","https://openalex.org/W4407953541","https://openalex.org/W4409657523","https://openalex.org/W4412376894","https://openalex.org/W4412377908","https://openalex.org/W7133233095"],"related_works":[],"abstract_inverted_index":{"Multi-interest":[0],"recommendation":[1,174,205],"is":[2],"essential":[3],"for":[4],"the":[5,17,31,36,66,109,118,145,167,171,227],"matching":[6],"stage.":[7],"By":[8],"generating":[9],"multiple":[10],"user":[11,22,219],"representations,":[12],"it":[13],"can":[14],"better":[15],"cover":[16],"diverse":[18,115],"interests":[19,94],"derived":[20],"from":[21,103,140,148],"interaction":[23],"history.":[24],"Ideally,":[25],"multi-interest":[26],"models":[27],"should":[28],"effectively":[29,217],"identify":[30],"underlying":[32],"latent":[33,98],"factors":[34,99],"\u2014":[35,42],"specific":[37],"themes,":[38],"intents,":[39],"or":[40],"preferences":[41],"within":[43],"historical":[44,142],"behaviors.":[45,101],"However,":[46],"conventional":[47],"methods":[48],"typically":[49],"rely":[50],"on":[51,199],"weighted":[52],"aggregation":[53,64],"(e.g.,":[54],"Attention),":[55],"which":[56],"we":[57,84,130,159],"argue":[58],"leads":[59],"to":[60,122,165],"over-smoothed":[61],"representations.":[62],"This":[63],"dilutes":[65],"intensity":[67],"of":[68,170,194,230,232,234],"significant":[69],"patterns":[70],"that":[71,91,107,135],"appear":[72],"only":[73],"locally,":[74],"blending":[75],"them":[76],"into":[77,152],"a":[78,87,132,153,161,212],"blurry":[79],"average.":[80],"To":[81,127],"address":[82],"this,":[83,129],"propose":[85],"DMI,":[86],"model-agnostic":[88],"diffusion":[89,105,146],"framework":[90],"distills":[92],"precise":[93],"by":[95,207],"amplifying":[96],"co-occurring":[97],"across":[100,196],"Distinct":[102],"prior":[104],"works":[106],"reconstruct":[108],"single":[110],"next":[111],"item\u2014which":[112],"risks":[113],"collapsing":[114],"interests\u2014DMI":[116],"reconstructs":[117],"interest":[119],"vectors":[120],"themselves":[121],"preserve":[123],"their":[124],"distributional":[125],"independence.":[126],"support":[128],"introduce":[131],"cross-transformer":[133],"module":[134],"adaptively":[136],"extracts":[137],"interest-specific":[138],"information":[139],"designated":[141],"interactions,":[143],"transforming":[144],"process":[147],"an":[149,190],"unconditional":[150],"one":[151],"guided,":[154],"interest-disentangled":[155],"pathway.":[156],"In":[157],"addition,":[158],"design":[160],"gradient":[162],"back-propagation":[163],"strategy":[164],"decouple":[166],"joint":[168],"optimization":[169],"reconstruction":[172],"and":[173,221],"losses,":[175],"thereby":[176],"improving":[177],"training":[178],"stability.":[179],"Extensive":[180],"offline":[181],"experiments":[182],"demonstrate":[183],"DMI's":[184],"superiority":[185],"over":[186],"existing":[187],"methods,":[188],"achieving":[189],"average":[191],"relative":[192],"improvement":[193],"11.2%":[195],"all":[197],"metrics":[198],"Amazon":[200],"Books":[201],"datasets":[202],"while":[203],"increasing":[204],"diversity":[206],"11.8%.":[208],"Successfully":[209],"deployed":[210],"in":[211],"real-world":[213],"recommender":[214],"system,":[215],"DMI":[216],"enhances":[218],"satisfaction":[220],"system":[222],"performance":[223],"at":[224],"scale,":[225],"serving":[226],"major":[228],"traffic":[229],"hundreds":[231],"millions":[233],"daily":[235],"active":[236],"users.":[237]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-11T00:00:00"}