{"id":"https://openalex.org/W4412396182","doi":"https://doi.org/10.1145/3726302.3729881","title":"A Learnable Fully Interacted Two-Tower Model for Pre-Ranking System","display_name":"A Learnable Fully Interacted Two-Tower Model for Pre-Ranking System","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412396182","doi":"https://doi.org/10.1145/3726302.3729881"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3729881","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729881","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729881","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 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729881","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054912350","display_name":"Chao Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chao Xiong","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-0372-9277","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102126618","display_name":"Xianwen Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xianwen Yu","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0005-6402-6642","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Xu","orcid":"https://orcid.org/0009-0007-4709-260X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Xu","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-4709-260X","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040949467","display_name":"Lei Cheng","orcid":"https://orcid.org/0009-0002-2186-699X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Cheng","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-2186-699X","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chuan Yuan","orcid":"https://orcid.org/0009-0000-9018-8374"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chuan Yuan","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0000-9018-8374","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044628261","display_name":"Linjian Mo","orcid":"https://orcid.org/0000-0002-6682-1448"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Linjian Mo","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6682-1448","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, 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":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2182","last_page":"2191"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9979000091552734,"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":0.9979000091552734,"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":0.988099992275238,"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"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.98580002784729,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.60811847448349},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5937342047691345},{"id":"https://openalex.org/keywords/tower","display_name":"Tower","score":0.49061980843544006},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4317903220653534},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1863689422607422},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.09695705771446228}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.60811847448349},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5937342047691345},{"id":"https://openalex.org/C2777831296","wikidata":"https://www.wikidata.org/wiki/Q12518","display_name":"Tower","level":2,"score":0.49061980843544006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4317903220653534},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1863689422607422},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.09695705771446228}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3726302.3729881","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729881","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729881","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 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2509.12948","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.12948","pdf_url":"https://arxiv.org/pdf/2509.12948","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:10.1145/3726302.3729881","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729881","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729881","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 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412396182.pdf","grobid_xml":"https://content.openalex.org/works/W4412396182.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W2074694452","https://openalex.org/W2136189984","https://openalex.org/W2187089797","https://openalex.org/W2295739661","https://openalex.org/W2475334473","https://openalex.org/W2512971201","https://openalex.org/W2622338386","https://openalex.org/W2723293840","https://openalex.org/W2950960796","https://openalex.org/W2962745591","https://openalex.org/W2963924287","https://openalex.org/W2994850640","https://openalex.org/W3021397474","https://openalex.org/W3023045848","https://openalex.org/W3036320503","https://openalex.org/W3088777230","https://openalex.org/W3098468692","https://openalex.org/W3155298021","https://openalex.org/W4213069590","https://openalex.org/W4226337336","https://openalex.org/W4306317707"],"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/W4396696052"],"abstract_inverted_index":{"Pre-ranking":[0],"plays":[1],"a":[2,38,87,126],"crucial":[3],"role":[4],"in":[5,24,33,81],"large-scale":[6],"recommender":[7],"systems":[8,35],"by":[9],"significantly":[10,169],"improving":[11],"the":[12,17,71,77,152,171],"efficiency":[13,42],"and":[14,43,52,118,138,154],"scalability":[15],"within":[16],"constraints":[18],"of":[19,73,111],"providing":[20],"high-quality":[21],"candidate":[22],"sets":[23],"real":[25],"time.":[26],"The":[27],"two-tower":[28],"model":[29],"is":[30,97,143],"widely":[31],"used":[32],"pre-ranking":[34,174],"due":[36],"to":[37,70,131,145],"good":[39],"balance":[40],"between":[41,76,136,151],"effectiveness":[44],"with":[45],"decoupled":[46],"architecture,":[47],"which":[48,99],"independently":[49],"processes":[50],"user":[51,137,153],"item":[53,128,139,155],"inputs":[54],"before":[55],"calculating":[56],"their":[57],"interaction":[58,75,135,150],"(e.g.":[59],"dot":[60],"product":[61],"or":[62],"similarity":[63],"measure).":[64],"However,":[65],"this":[66,85],"independence":[67],"also":[68],"leads":[69],"lack":[72],"information":[74,102],"two":[78,112],"towers,":[79],"resulting":[80],"less":[82],"effectiveness.":[83],"In":[84],"paper,":[86],"novel":[88],"architecture":[89],"named":[90],"learnable":[91,127],"Fully":[92],"Interacted":[93],"Two-tower":[94],"Model":[95],"(FIT)":[96],"proposed,":[98],"enables":[100],"rich":[101],"interactions":[103],"while":[104],"ensuring":[105],"inference":[106],"efficiency.":[107],"FIT":[108,168],"mainly":[109],"consists":[110],"parts:":[113],"Meta":[114],"Query":[115],"Module":[116],"(MQM)":[117],"Lightweight":[119],"Similarity":[120],"Scorer":[121],"(LSS).":[122],"Specifically,":[123],"MQM":[124],"introduces":[125],"meta":[129],"matrix":[130],"achieve":[132],"expressive":[133],"early":[134],"features.":[140],"Moreover,":[141],"LSS":[142],"designed":[144],"further":[146],"obtain":[147],"effective":[148],"late":[149],"towers.":[156],"Finally,":[157],"experimental":[158],"results":[159],"on":[160],"several":[161],"public":[162],"datasets":[163],"show":[164],"that":[165],"our":[166],"proposed":[167],"outperforms":[170],"state-of-the-art":[172],"baseline":[173],"models.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}