{"id":"https://openalex.org/W7138221232","doi":"https://doi.org/10.1609/aaai.v40i17.38518","title":"Invariant Feature Learning for Counterfactual Watch-time Prediction in Video Recommendation","display_name":"Invariant Feature Learning for Counterfactual Watch-time Prediction in Video Recommendation","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138221232","doi":"https://doi.org/10.1609/aaai.v40i17.38518"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i17.38518","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i17.38518","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i17.38518","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078395685","display_name":"Chenghou Jin","orcid":"https://orcid.org/0000-0001-9986-6071"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chenghou Jin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129718754","display_name":"Yixin Ren","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yixin Ren","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129679143","display_name":"Hongxu Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongxu Ma","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089892186","display_name":"Yewei Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yewei Xia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129658082","display_name":"Yi Guan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Guan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129654853","display_name":"Hao Y. Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Zhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016081741","display_name":"Jiandong Ding","orcid":"https://orcid.org/0000-0001-8123-9889"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiandong Ding","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121302179","display_name":"Jihong Guan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jihong Guan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5110338878","display_name":"ShuiGeng ZHOU","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuigeng Zhou","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5078395685"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.57541899,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"17","first_page":"14964","last_page":"14972"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.7039999961853027,"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":0.7039999961853027,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.04010000079870224,"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"}},{"id":"https://openalex.org/T13553","display_name":"Age of Information Optimization","score":0.029899999499320984,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.7325999736785889},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5472999811172485},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4767000079154968},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.38519999384880066},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.37689998745918274},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.3628000020980835},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.3582000136375427},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.34380000829696655},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.3249000012874603}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.7325999736785889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6841999888420105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6157000064849854},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5866000056266785},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5472999811172485},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4767000079154968},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.37689998745918274},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.3582000136375427},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.34380000829696655},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.30640000104904175},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2816999852657318},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2542000114917755},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i17.38518","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i17.38518","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i17.38518","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i17.38518","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video":[0],"recommendation":[1,26],"systems":[2],"heavily":[3],"rely":[4],"on":[5,76,176],"user":[6],"watch":[7,12,35,77],"time":[8,13,78],"feedback,":[9],"making":[10,171],"accurate":[11,163],"prediction":[14,46,100],"a":[15,52,60,98,133,142],"crucial":[16],"task.":[17],"However,":[18,102],"this":[19,65,103,119],"task":[20],"inherently":[21],"suffers":[22],"from":[23,51,79],"bias,":[24],"as":[25,40,59],"models":[27],"tend":[28],"to":[29,33,108,112,154],"favor":[30],"long-duration":[31],"videos":[32],"maximize":[34],"time.":[36],"This":[37,160],"issue,":[38],"known":[39],"duration":[41,57,87,150],"bias":[42,66],"in":[43],"the":[44,71,123,126,166,185],"watch-time":[45],"context,":[47],"can":[48],"be":[49],"explained":[50],"causal":[53,168],"perspective,":[54],"where":[55],"video":[56,86],"acts":[58],"confounder.":[61],"Recent":[62],"works":[63],"address":[64],"using":[67],"backdoor":[68],"adjustment,":[69],"isolating":[70],"direct":[72,167],"effect":[73,169],"of":[74,128,165,187],"content":[75],"observational":[80],"data.":[81],"These":[82],"methods":[83],"typically":[84],"discretize":[85],"into":[88],"groups,":[89,151],"estimate":[90],"group-wise":[91],"effects,":[92],"and":[93,131,157,170,179],"then":[94],"aggregate":[95],"them":[96],"via":[97],"unified":[99],"model.":[101],"aggregation":[104],"strategy":[105],"is":[106],"prone":[107],"model":[109],"misspecification":[110],"due":[111],"feature":[113],"distribution":[114],"shift":[115],"across":[116,149],"groups.":[117],"In":[118],"paper,":[120],"we":[121],"reinterpret":[122],"problem":[124],"through":[125],"lens":[127],"invariant":[129],"learning":[130],"propose":[132],"novel":[134],"framework:":[135],"Duration-Invariant":[136],"Feature":[137],"Learning":[138],"(DIFL).":[139],"DIFL":[140],"employs":[141],"kernel-based":[143],"regularization":[144],"that":[145],"enforces":[146],"representation":[147],"invariance":[148],"reducing":[152],"sensitivity":[153],"group":[155],"design":[156],"improving":[158],"generalization.":[159],"enables":[161],"more":[162],"modeling":[164],"counterfactual":[172],"inference.":[173],"Extensive":[174],"experiments":[175],"both":[177],"public":[178],"real":[180],"large-scale":[181],"production":[182],"datasets":[183],"demonstrate":[184],"effectiveness":[186],"our":[188],"approach,":[189],"which":[190],"achieves":[191],"SOTA":[192],"performance.":[193]},"counts_by_year":[],"updated_date":"2026-03-18T06:31:55.123368","created_date":"2026-03-18T00:00:00"}
