{"id":"https://openalex.org/W4385565469","doi":"https://doi.org/10.1145/3580305.3599798","title":"CT4Rec: Simple yet Effective Consistency Training for Sequential Recommendation","display_name":"CT4Rec: Simple yet Effective Consistency Training for Sequential Recommendation","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385565469","doi":"https://doi.org/10.1145/3580305.3599798"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599798","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599798","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103180089","display_name":"Chong Liu","orcid":"https://orcid.org/0000-0003-4601-2886"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liu Chong","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102993367","display_name":"Xiaoyang Liu","orcid":"https://orcid.org/0000-0002-2005-4933"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoyang Liu","raw_affiliation_strings":["OPPO Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"OPPO Inc., Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101882019","display_name":"Rongqin Zheng","orcid":"https://orcid.org/0000-0002-7116-8666"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongqin Zheng","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427813","display_name":"Lixin Zhang","orcid":"https://orcid.org/0000-0002-3938-3761"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Zhang","raw_affiliation_strings":["Tencent Inc., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102023923","display_name":"Xiaobo Liang","orcid":"https://orcid.org/0009-0001-1550-2877"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobo Liang","raw_affiliation_strings":["Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100657514","display_name":"Juntao Li","orcid":"https://orcid.org/0000-0002-6286-7529"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juntao Li","raw_affiliation_strings":["Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102750692","display_name":"Lijun Wu","orcid":"https://orcid.org/0000-0002-3530-590X"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijun Wu","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100402911","display_name":"Min Zhang","orcid":"https://orcid.org/0000-0002-3895-5510"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Zhang","raw_affiliation_strings":["Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023086553","display_name":"Leyu Lin","orcid":"https://orcid.org/0000-0001-5471-500X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leyu Lin","raw_affiliation_strings":["Tencent Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tencent Inc., Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5103180089"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":5.8891,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.96304379,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3901","last_page":"3913"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9470999836921692,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9373000264167786,"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/simple","display_name":"Simple (philosophy)","score":0.7730065584182739},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7643990516662598},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6551744341850281},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6194690465927124},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34350472688674927}],"concepts":[{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.7730065584182739},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7643990516662598},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6551744341850281},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6194690465927124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34350472688674927},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580305.3599798","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599798","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W2027731328","https://openalex.org/W2090883204","https://openalex.org/W2171279286","https://openalex.org/W2295739661","https://openalex.org/W2469952266","https://openalex.org/W2475334473","https://openalex.org/W2512971201","https://openalex.org/W2584643785","https://openalex.org/W2605234117","https://openalex.org/W2605350416","https://openalex.org/W2625746539","https://openalex.org/W2734755249","https://openalex.org/W2739901700","https://openalex.org/W2745534091","https://openalex.org/W2783272285","https://openalex.org/W2783944588","https://openalex.org/W2793768763","https://openalex.org/W2798385737","https://openalex.org/W2808310571","https://openalex.org/W2809307135","https://openalex.org/W2892181857","https://openalex.org/W2898085636","https://openalex.org/W2899457523","https://openalex.org/W2902572901","https://openalex.org/W2903749028","https://openalex.org/W2949340817","https://openalex.org/W2963367478","https://openalex.org/W2963981376","https://openalex.org/W2964044287","https://openalex.org/W2964296635","https://openalex.org/W2964352502","https://openalex.org/W2964926209","https://openalex.org/W2984100107","https://openalex.org/W2986515219","https://openalex.org/W2987999026","https://openalex.org/W2996931760","https://openalex.org/W3036320503","https://openalex.org/W3044893918","https://openalex.org/W3065542300","https://openalex.org/W3081362488","https://openalex.org/W3098231197","https://openalex.org/W3098468692","https://openalex.org/W3100260481","https://openalex.org/W3101704389","https://openalex.org/W3101707147","https://openalex.org/W3104030692","https://openalex.org/W3113192049","https://openalex.org/W3114632476","https://openalex.org/W3152943193","https://openalex.org/W3153468025","https://openalex.org/W3154419237","https://openalex.org/W3156807319","https://openalex.org/W3156844209","https://openalex.org/W3170587616","https://openalex.org/W3171249018"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W230091440","https://openalex.org/W1585007175","https://openalex.org/W2382521049","https://openalex.org/W2390279801","https://openalex.org/W2233261550","https://openalex.org/W2144385241","https://openalex.org/W2358668433","https://openalex.org/W2810751659","https://openalex.org/W258997015"],"abstract_inverted_index":{"Sequential":[0],"recommendation":[1,26,85,159],"methods":[2,57],"are":[3,109],"increasingly":[4],"important":[5],"in":[6,102],"cutting-edge":[7],"recommender":[8],"systems.":[9],"Through":[10],"leveraging":[11],"historical":[12],"records,":[13],"the":[14,45,166,173],"systems":[15],"can":[16],"capture":[17],"user":[18,38,80],"interests":[19],"and":[20,42,58,65,82,115,123,142,169],"perform":[21],"recommendations":[22],"accordingly.":[23],"State-of-the-art":[24],"sequential":[25,84,99],"models":[27,46,137],"proposed":[28,133],"very":[29],"recently":[30],"combine":[31],"contrastive":[32,49,152],"learning":[33,50],"techniques":[34],"for":[35,77,98,190],"obtaining":[36,78],"high-quality":[37],"representations.":[39],"Though":[40],"effective":[41,93],"performing":[43],"well,":[44],"based":[47,150],"on":[48,119,151,156,165,172],"require":[51],"careful":[52],"selection":[53],"of":[54],"data":[55,116],"augmentation":[56],"pretext":[59],"tasks,":[60],"efficient":[61],"negative":[62],"sampling":[63],"strategies,":[64],"massive":[66],"hyper-parameters":[67],"validation.":[68],"In":[69],"this":[70],"paper,":[71],"we":[72,88],"propose":[73],"an":[74],"ultra-simple":[75],"alternative":[76],"better":[79],"representations":[81],"improving":[83],"performance.":[86],"Specifically,":[87],"present":[89],"a":[90,139,184],"simple":[91,185],"yet":[92],"Consistency":[94],"T":[95],"braining":[96],"method":[97,134,186],"Recommendation":[100],"(CT4Rec)":[101],"which":[103],"only":[104],"two":[105],"extra":[106],"training":[107,146],"objectives":[108],"utilized":[110],"without":[111],"any":[112],"structural":[113],"modifications":[114],"augmentation.":[117],"Experiments":[118],"three":[120],"benchmark":[121],"datasets":[122],"one":[124],"large":[125,140],"newly":[126],"crawled":[127],"industrial":[128],"corpus":[129],"demonstrate":[130],"that":[131,182],"our":[132],"outperforms":[135],"SOTA":[136],"by":[138],"margin":[141],"with":[143],"much":[144],"less":[145],"time":[147],"than":[148],"these":[149],"learning.":[153],"Online":[154],"evaluation":[155],"real-world":[157],"content":[158],"system":[160],"also":[161],"achieves":[162],"2.717%":[163],"improvement":[164],"click-through":[167],"rate":[168],"3.679%":[170],"increase":[171],"average":[174],"click":[175],"number":[176],"per":[177],"capita.":[178],"Further":[179],"exploration":[180],"reveals":[181],"such":[183],"has":[187],"great":[188],"potential":[189],"CTR":[191],"prediction.":[192],"Our":[193],"code":[194],"is":[195],"available":[196],"at":[197],"https://github.com/ct4rec/CT4Rec.git.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2023-08-05T00:00:00"}