{"id":"https://openalex.org/W7167914323","doi":"https://doi.org/10.1145/3805712.3809857","title":"Equip Pre-ranking with Target Attention by Residual Quantization","display_name":"Equip Pre-ranking with Target Attention by Residual Quantization","publication_year":2026,"publication_date":"2026-07-10","ids":{"openalex":"https://openalex.org/W7167914323","doi":"https://doi.org/10.1145/3805712.3809857"},"language":null,"primary_location":{"id":"doi:10.1145/3805712.3809857","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805712.3809857","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/10.1145/3805712.3809857","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140434631","display_name":"Yutong Li","orcid":"https://orcid.org/0009-0002-1658-5720"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yutong Li","raw_affiliation_strings":["Taobao &amp;#38; Tmall Group of Alibaba, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-1658-5720","affiliations":[{"raw_affiliation_string":"Taobao &amp;#38; Tmall Group of Alibaba, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100673743","display_name":"Yu Zhu","orcid":"https://orcid.org/0000-0001-9746-1695"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zhu","raw_affiliation_strings":["Taobao &amp;#38; Tmall Group of Alibaba, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9746-1695","affiliations":[{"raw_affiliation_string":"Taobao &amp;#38; Tmall Group of Alibaba, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113353825","display_name":"Yichen Qiao","orcid":null},"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":"Yichen Qiao","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-7007-4248","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065194313","display_name":"Ziyu Guan","orcid":"https://orcid.org/0000-0003-2413-4698"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyu Guan","raw_affiliation_strings":["Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-2413-4698","affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133738188","display_name":"Lv Shao","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lv Shao","raw_affiliation_strings":["Taobao &amp;#38; Tmall Group of Alibaba, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0008-5389-6476","affiliations":[{"raw_affiliation_string":"Taobao &amp;#38; Tmall Group of Alibaba, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079780539","display_name":"Tong Liu","orcid":"https://orcid.org/0000-0003-2425-0357"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Liu","raw_affiliation_strings":["Taobao &amp;#38; Tmall Group of Alibaba, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2425-0357","affiliations":[{"raw_affiliation_string":"Taobao &amp;#38; Tmall Group of Alibaba, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073856221","display_name":"Bo Zheng","orcid":"https://orcid.org/0000-0002-4037-6315"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Zheng","raw_affiliation_strings":["Taobao &amp;#38; Tmall Group of Alibaba, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4037-6315","affiliations":[{"raw_affiliation_string":"Taobao &amp;#38; Tmall Group of Alibaba, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":"3947","last_page":"3951"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.7369999885559082,"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":0.7369999885559082,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.05079999938607216,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.019600000232458115,"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/bottleneck","display_name":"Bottleneck","score":0.661899983882904},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.571399986743927},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5400999784469604},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.41530001163482666},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.413100004196167},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3700000047683716},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.34779998660087585}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7793999910354614},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.661899983882904},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.571399986743927},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5400999784469604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49790000915527344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4659999907016754},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.413100004196167},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3700000047683716},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.34779998660087585},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3458999991416931},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34459999203681946},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25209999084472656},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805712.3809857","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805712.3809857","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:10.1145/3805712.3809857","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805712.3809857","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":[{"score":0.6376124620437622,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2622338386","https://openalex.org/W2723293840","https://openalex.org/W2908332126","https://openalex.org/W2922386288","https://openalex.org/W2962745591","https://openalex.org/W2994850640","https://openalex.org/W3093519337","https://openalex.org/W3171608958","https://openalex.org/W3215615641","https://openalex.org/W4306317673","https://openalex.org/W4306317707","https://openalex.org/W4312974539","https://openalex.org/W4385562613","https://openalex.org/W4400909953","https://openalex.org/W4403577780","https://openalex.org/W4412877069","https://openalex.org/W7133188876","https://openalex.org/W7133208784","https://openalex.org/W7133239020"],"related_works":[],"abstract_inverted_index":{"The":[0,157],"pre-ranking":[1,68,80,103],"stage":[2,104],"in":[3,28,132,142],"industrial":[4],"recommendation":[5],"systems":[6],"faces":[7],"a":[8,51,66,110],"fundamental":[9],"conflict":[10],"between":[11,114],"efficiency":[12],"and":[13,116,121,152,159],"effectiveness.":[14],"While":[15],"powerful":[16],"models":[17],"like":[18],"Target":[19],"Attention":[20],"(TA)":[21],"excel":[22],"at":[23,126,163],"capturing":[24],"complex":[25],"feature":[26],"interactions":[27],"the":[29,56,95,101,106],"ranking":[30,133],"stage,":[31],"their":[32],"high":[33],"computational":[34],"cost":[35],"makes":[36],"them":[37],"infeasible":[38],"for":[39,55,105],"pre-ranking,":[40],"which":[41],"often":[42],"relies":[43],"on":[44],"simplistic":[45],"vector-product":[46],"models.":[47],"This":[48,90],"disparity":[49],"creates":[50],"significant":[52,130],"performance":[53],"bottleneck":[54],"entire":[57],"system.":[58],"To":[59],"bridge":[60],"this":[61],"gap,":[62],"we":[63],"propose":[64],"TARQ,":[65],"novel":[67],"framework.":[69],"Inspired":[70],"by":[71,87],"generative":[72],"models,":[73],"TARQ's":[74,129],"key":[75],"innovation":[76],"is":[77],"to":[78,85,93],"equip":[79],"with":[81],"an":[82],"architecture":[83],"approximate":[84],"TA":[86,99],"Residual":[88],"Quantization.":[89],"allows":[91],"us":[92],"bring":[94],"modeling":[96],"power":[97],"of":[98,146,148],"into":[100],"latency-critical":[102],"first":[107],"time,":[108],"establishing":[109],"new":[111],"state-of-the-art":[112],"trade-off":[113],"accuracy":[115],"efficiency.":[117],"Extensive":[118],"offline":[119],"experiments":[120],"large-scale":[122],"online":[123],"A/B":[124],"tests":[125],"Taobao":[127],"demonstrate":[128],"improvements":[131],"performance.":[134],"Consequently,":[135],"our":[136],"model":[137],"has":[138],"been":[139],"fully":[140],"deployed":[141],"production,":[143],"serving":[144],"tens":[145],"millions":[147],"daily":[149],"active":[150],"users":[151],"yielding":[153],"substantial":[154],"business":[155],"improvements.":[156],"code":[158],"data":[160],"are":[161],"available":[162],"https://github.com/zyody/tarq_sigir2026.":[164]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-07-11T00:00:00"}
