{"id":"https://openalex.org/W4392384854","doi":"https://doi.org/10.1145/3616855.3635779","title":"Pre-trained Recommender Systems: A Causal Debiasing Perspective","display_name":"Pre-trained Recommender Systems: A Causal Debiasing Perspective","publication_year":2024,"publication_date":"2024-03-04","ids":{"openalex":"https://openalex.org/W4392384854","doi":"https://doi.org/10.1145/3616855.3635779"},"language":"en","primary_location":{"id":"doi:10.1145/3616855.3635779","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3616855.3635779","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3616855.3635779","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3616855.3635779","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039721156","display_name":"Ziqian Lin","orcid":"https://orcid.org/0000-0002-6977-0156"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ziqian Lin","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100669038","display_name":"Hao Ding","orcid":"https://orcid.org/0000-0001-9932-2971"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Ding","raw_affiliation_strings":["AWS AI Labs, Santa Barbara, USA"],"affiliations":[{"raw_affiliation_string":"AWS AI Labs, Santa Barbara, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102929916","display_name":"Trong Nghia Hoang","orcid":"https://orcid.org/0000-0002-9175-6246"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nghia Trong Hoang","raw_affiliation_strings":["Washington State University, Pullman, USA"],"affiliations":[{"raw_affiliation_string":"Washington State University, Pullman, USA","institution_ids":["https://openalex.org/I72951846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049020775","display_name":"Branislav Kveton","orcid":"https://orcid.org/0000-0002-3965-1367"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Branislav Kveton","raw_affiliation_strings":["AWS AI Labs, Santa Barbara, USA"],"affiliations":[{"raw_affiliation_string":"AWS AI Labs, Santa Barbara, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000621526","display_name":"Anoop Deoras","orcid":"https://orcid.org/0009-0007-4566-8767"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anoop Deoras","raw_affiliation_strings":["AWS AI Labs, Santa Barbara, USA"],"affiliations":[{"raw_affiliation_string":"AWS AI Labs, Santa Barbara, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100599815","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0002-7308-938X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["AWS AI Labs, Santa Barbara, USA"],"affiliations":[{"raw_affiliation_string":"AWS AI Labs, Santa Barbara, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5039721156"],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":null,"apc_paid":null,"fwci":3.8971,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.93685748,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"424","last_page":"433"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9983000159263611,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8585138320922852},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7612531185150146},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.7369343042373657},{"id":"https://openalex.org/keywords/debiasing","display_name":"Debiasing","score":0.7356559038162231},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6210573315620422},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6011114120483398},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5773301124572754},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5372670888900757},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3440811038017273}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8585138320922852},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7612531185150146},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7369343042373657},{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.7356559038162231},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6210573315620422},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6011114120483398},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5773301124572754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5372670888900757},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3440811038017273},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3616855.3635779","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3616855.3635779","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3616855.3635779","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3616855.3635779","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3616855.3635779","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3616855.3635779","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392384854.pdf","grobid_xml":"https://content.openalex.org/works/W4392384854.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W2157881433","https://openalex.org/W2517898103","https://openalex.org/W2725606191","https://openalex.org/W2796608345","https://openalex.org/W2899457523","https://openalex.org/W2905461678","https://openalex.org/W2945623882","https://openalex.org/W2963058055","https://openalex.org/W2963367478","https://openalex.org/W2970641574","https://openalex.org/W2986176093","https://openalex.org/W2996891863","https://openalex.org/W2997842202","https://openalex.org/W3025937945","https://openalex.org/W3034379146","https://openalex.org/W3034423547","https://openalex.org/W3034744380","https://openalex.org/W3034896171","https://openalex.org/W3034942609","https://openalex.org/W3043590771","https://openalex.org/W3089238887","https://openalex.org/W3092103025","https://openalex.org/W3094484861","https://openalex.org/W3098400049","https://openalex.org/W3101707147","https://openalex.org/W3156622960","https://openalex.org/W3156939347","https://openalex.org/W3171973478","https://openalex.org/W3188301284","https://openalex.org/W3200686557","https://openalex.org/W4213052788","https://openalex.org/W4320168472","https://openalex.org/W4386730463"],"related_works":["https://openalex.org/W4362554880","https://openalex.org/W4281684980","https://openalex.org/W4386875279","https://openalex.org/W2171721708","https://openalex.org/W4390963114","https://openalex.org/W3214527415","https://openalex.org/W4287887864","https://openalex.org/W1495104519","https://openalex.org/W4377864593","https://openalex.org/W3196817267"],"abstract_inverted_index":{"Recent":[0],"studies":[1],"on":[2,24,108],"pre-trained":[3,23,90],"vision/language":[4],"models":[5,20],"have":[6],"demonstrated":[7],"the":[8,67,77,87],"practical":[9],"benefit":[10],"of":[11,41,71,79,89],"a":[12,28,38,74,98],"new,":[13],"promising":[14],"solution-building":[15],"paradigm":[16,75],"in":[17,52,64,128],"AI":[18],"where":[19],"can":[21,118],"be":[22,120],"broad":[25],"data":[26,47,112],"describing":[27],"generic":[29,99,109],"task":[30],"space":[31],"and":[32,69],"then":[33,119],"adapted":[34,122],"successfully":[35],"to":[36,76,96,123],"solve":[37],"wide":[39],"range":[40],"downstream":[42],"tasks,":[43],"even":[44],"when":[45],"training":[46,107],"is":[48,83],"severely":[49],"limited":[50,133],"(e.g.,":[51],"zero-":[53],"or":[54],"few-shot":[55,125],"learning":[56,126],"scenarios).":[57],"Inspired":[58],"by":[59,106],"such":[60,73],"progress,":[61],"we":[62,94],"investigate":[63],"this":[65],"paper":[66],"possibilities":[68],"challenges":[70],"adapting":[72],"context":[78],"recommender":[80,100],"systems,":[81],"which":[82,117],"less":[84],"investigated":[85],"from":[86,114],"perspective":[88],"model.":[91],"In":[92],"particular,":[93],"propose":[95],"develop":[97],"that":[101],"captures":[102],"universal":[103],"interaction":[104,111],"patterns":[105],"user-item":[110],"extracted":[113],"different":[115],"domains,":[116],"fast":[121],"improve":[124],"performance":[127],"unseen":[129],"new":[130],"domains":[131],"(with":[132],"data).":[134]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
