{"id":"https://openalex.org/W7162469731","doi":"https://doi.org/10.48550/arxiv.2605.25726","title":"SIREN: Unified Multi-Granularity Semantic Interaction for Multi-Modal Lifelong User Interest Modeling","display_name":"SIREN: Unified Multi-Granularity Semantic Interaction for Multi-Modal Lifelong User Interest Modeling","publication_year":2026,"publication_date":"2026-05-25","ids":{"openalex":"https://openalex.org/W7162469731","doi":"https://doi.org/10.48550/arxiv.2605.25726"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.25726","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25726","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.25726","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136998964","display_name":"Yaqian Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yaqian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137015804","display_name":"Ruyi Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Ruyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137000492","display_name":"Tianyi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Tianyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137063583","display_name":"Bohan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Bohan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022642030","display_name":"Maoquan Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Maoquan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137077232","display_name":"Ke Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054612059","display_name":"Shifeng Wen","orcid":"https://orcid.org/0000-0002-1330-8333"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Shifeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137004191","display_name":"Junwei Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Junwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100651061","display_name":"Lijie Wang","orcid":"https://orcid.org/0000-0003-1702-0422"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lijie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137014155","display_name":"Qi Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Qi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040294543","display_name":"Yeshou Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Yeshou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137081247","display_name":"Chengguo Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Chengguo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137066093","display_name":"Lifeng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lifeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137009434","display_name":"Hui Li","orcid":"https://orcid.org/0009-0003-1487-5940"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Hui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137052246","display_name":"Lei Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056695193","display_name":"Haijie Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Haijie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.8055999875068665,"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":0.8055999875068665,"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":0.03709999844431877,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.018799999728798866,"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/leverage","display_name":"Leverage (statistics)","score":0.6536999940872192},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4867999851703644},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.46950000524520874},{"id":"https://openalex.org/keywords/relevance-feedback","display_name":"Relevance feedback","score":0.38179999589920044},{"id":"https://openalex.org/keywords/user-modeling","display_name":"User modeling","score":0.364300012588501},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.33809998631477356},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.32850000262260437}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8062000274658203},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6536999940872192},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5896999835968018},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4867999851703644},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.46950000524520874},{"id":"https://openalex.org/C2779532271","wikidata":"https://www.wikidata.org/wiki/Q445558","display_name":"Relevance feedback","level":4,"score":0.38179999589920044},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.364300012588501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34290000796318054},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.33809998631477356},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.32850000262260437},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.30649998784065247},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.29600000381469727},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.28189998865127563},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27070000767707825},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2671999931335449},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.26089999079704285}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.25726","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25726","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.25726","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25726","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.45662397146224976,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Industrial":[0],"recommender":[1],"systems":[2],"increasingly":[3],"leverage":[4],"lifelong":[5,24,83],"user":[6,16,84],"behavior":[7,50],"histories":[8],"and":[9,36,49,52,66,106,131,182],"rich":[10],"multi-modal":[11,21,35,47,64,82,99],"content":[12],"to":[13,30,55],"capture":[14],"evolving":[15],"preferences.":[17],"However,":[18],"effectively":[19],"integrating":[20],"features":[22,141],"into":[23],"interest":[25,85],"modeling":[26,45],"remains":[27],"challenging":[28],"due":[29],"the":[31,57,88,117,143,150],"inherent":[32],"misalignment":[33],"between":[34],"collaborative":[37,139],"spaces.":[38],"Existing":[39],"paradigms":[40],"typically":[41],"rely":[42],"on":[43,149],"separate":[44],"of":[46],"sequence":[48],"sequence,":[51],"late":[53],"fusion":[54],"alleviate":[56],"modality":[58],"gap,":[59],"which":[60],"results":[61],"in":[62,174,178,184,198],"coarse-grained":[63],"representation":[65],"limited":[67],"integration.":[68],"In":[69,87],"this":[70],"paper,":[71],"we":[72,93,122],"propose":[73],"SIREN,":[74],"a":[75,157],"unified":[76,136],"multi-granularity":[77],"semantic":[78],"interaction":[79,137],"framework":[80],"for":[81,103,112,195],"modeling.":[86],"General":[89],"Search":[90,119],"Unit":[91,120],"stage,":[92,121],"introduce":[94],"two":[95],"alternative":[96],"retrieval":[97,102,104,111],"strategies:":[98],"similarity-based":[100],"soft":[101],"effectiveness,":[105],"Semantic":[107],"ID":[108,140],"(SemID)-based":[109],"hard":[110],"efficient":[113],"industrial":[114],"serving.":[115],"For":[116],"Exact":[118],"explicitly":[123],"incorporate":[124],"target-aware":[125],"relevance":[126],"via":[127],"coarse":[128],"similarity":[129],"buckets":[130],"fine-grained":[132],"prefix-encoded":[133],"SemIDs,":[134],"enabling":[135],"with":[138],"within":[142],"target-conditioned":[144],"transformer":[145],"architecture.":[146],"Extensive":[147],"experiments":[148],"offline":[151],"dataset":[152],"demonstrate":[153,164],"that":[154],"SIREN":[155,190],"achieves":[156],"state-of-the-art":[158],"GAUC.":[159],"Online":[160],"A/B":[161],"tests":[162],"further":[163],"consistent":[165],"GMV":[166],"gains":[167],"across":[168],"multiple":[169],"production":[170],"scenarios,":[171],"including":[172],"+2.28%":[173],"Weixin":[175,179,185],"Moments,":[176],"+3.87%":[177],"Official":[180],"Accounts,":[181],"+1.61%":[183],"Channels.":[186],"From":[187],"July":[188],"2025,":[189],"has":[191],"been":[192],"fully":[193],"launched":[194],"full-traffic":[196],"serving":[197],"Tencent's":[199],"advertising":[200],"platform.":[201]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-27T00:00:00"}