{"id":"https://openalex.org/W4411279763","doi":"https://doi.org/10.1145/3699682.3730978","title":"Finding Interest Needle in Popularity Haystack: Improving Retrieval by Modeling Item Exposure","display_name":"Finding Interest Needle in Popularity Haystack: Improving Retrieval by Modeling Item Exposure","publication_year":2025,"publication_date":"2025-06-13","ids":{"openalex":"https://openalex.org/W4411279763","doi":"https://doi.org/10.1145/3699682.3730978"},"language":"en","primary_location":{"id":"doi:10.1145/3699682.3730978","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3699682.3730978","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3699682.3730978","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3699682.3730978","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Rahul Agarwal","orcid":"https://orcid.org/0009-0002-9963-3889"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rahul Agarwal","raw_affiliation_strings":["VideoRecs, Meta, Bellevue, WA, USA"],"raw_orcid":"https://orcid.org/0009-0002-9963-3889","affiliations":[{"raw_affiliation_string":"VideoRecs, Meta, Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118141365","display_name":"Amit Jaspal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amit Jaspal","raw_affiliation_strings":["Meta, Menlo Park, CA, USA"],"raw_orcid":"https://orcid.org/0009-0002-4253-3836","affiliations":[{"raw_affiliation_string":"Meta, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210099336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101903240","display_name":"Saurabh Gupta","orcid":"https://orcid.org/0009-0002-3337-8408"},"institutions":[{"id":"https://openalex.org/I3197470489","display_name":"Alpha Omega Alpha Medical Honor Society","ror":"https://ror.org/057q9nn35","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I3197470489"]},{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saurabh Gupta","raw_affiliation_strings":["Meta, Menlo Park, USA"],"raw_orcid":"https://orcid.org/0009-0002-3337-8408","affiliations":[{"raw_affiliation_string":"Meta, Menlo Park, USA","institution_ids":["https://openalex.org/I3197470489","https://openalex.org/I4210099336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5118141366","display_name":"Omkar Vichare","orcid":"https://orcid.org/0009-0005-9835-1355"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Omkar Vichare","raw_affiliation_strings":["Meta, Bellevue, USA"],"raw_orcid":"https://orcid.org/0009-0005-9835-1355","affiliations":[{"raw_affiliation_string":"Meta, Bellevue, USA","institution_ids":["https://openalex.org/I4210108985"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210108985"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1860035,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"364","last_page":"366"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9983999729156494,"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":0.9983999729156494,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.953499972820282,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9395999908447266,"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/haystack","display_name":"Haystack","score":0.9952651262283325},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.772944986820221},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6538919806480408},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.37756937742233276},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22036457061767578},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.05966925621032715}],"concepts":[{"id":"https://openalex.org/C13424479","wikidata":"https://www.wikidata.org/wiki/Q5687237","display_name":"Haystack","level":2,"score":0.9952651262283325},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.772944986820221},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6538919806480408},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.37756937742233276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22036457061767578},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.05966925621032715},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3699682.3730978","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3699682.3730978","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3699682.3730978","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2503.23630","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.23630","pdf_url":"https://arxiv.org/pdf/2503.23630","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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:10.1145/3699682.3730978","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3699682.3730978","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3699682.3730978","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411279763.pdf","grobid_xml":"https://content.openalex.org/works/W4411279763.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W2251567929","https://openalex.org/W2972801466","https://openalex.org/W3023045848","https://openalex.org/W3041537557","https://openalex.org/W3156774354","https://openalex.org/W3161056598","https://openalex.org/W4379933301","https://openalex.org/W6948348096"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4253878822","https://openalex.org/W1965563707","https://openalex.org/W1736550718","https://openalex.org/W4210692028","https://openalex.org/W4408323858","https://openalex.org/W2808729870","https://openalex.org/W2479343091"],"abstract_inverted_index":{"Recommender":[0],"systems":[1],"operate":[2,41],"in":[3,97,109,119,127],"closed":[4],"feedback":[5],"loops,":[6],"where":[7],"user":[8,137],"interactions":[9],"reinforce":[10],"popularity":[11,149],"bias,":[12],"leading":[13],"to":[14],"over-recommendation":[15],"of":[16,130],"already":[17],"popular":[18],"items":[19,122],"while":[20,134],"under-exposing":[21],"niche":[22],"or":[23,46],"novel":[24],"content.":[25],"Existing":[26],"bias":[27,150],"mitigation":[28],"methods,":[29],"such":[30],"as":[31],"Inverse":[32],"Propensity":[33],"Scoring":[34],"(IPS)":[35],"and":[36,72,95,123],"Off-Policy":[37],"Correction":[38],"(OPC),":[39],"primarily":[40],"at":[42,76,151],"the":[43,128,152],"ranking":[44,75],"stage":[45],"during":[47],"training,":[48],"lacking":[49],"explicit":[50],"real-time":[51],"control":[52],"over":[53],"exposure":[54,70,85],"dynamics.":[55],"In":[56],"this":[57,82],"work,":[58,81],"we":[59],"introduce":[60],"an":[61],"exposure-aware":[62],"retrieval":[63,153],"scoring":[64],"approach,":[65],"which":[66],"explicitly":[67],"models":[68],"item":[69],"probability":[71],"adjusts":[73],"retrieval-stage":[74],"inference":[77],"time.":[78],"Unlike":[79],"prior":[80],"method":[83],"decouples":[84],"effects":[86],"from":[87],"engagement":[88,96,138],"likelihood,":[89],"enabling":[90],"controlled":[91],"trade-offs":[92],"between":[93],"fairness":[94],"large-scale":[98],"recommendation":[99,113],"platforms.":[100],"We":[101],"validate":[102],"our":[103],"approach":[104],"through":[105],"online":[106],"A/B":[107],"experiments":[108],"a":[110,116,124,143,156],"real-world":[111],"video":[112],"system,":[114],"demonstrating":[115],"25%":[117],"increase":[118],"uniquely":[120],"retrieved":[121],"40%":[125],"reduction":[126],"dominance":[129],"over-popular":[131],"content,":[132],"all":[133],"maintaining":[135],"overall":[136],"levels.":[139],"Our":[140],"results":[141],"establish":[142],"scalable,":[144],"deployable":[145],"solution":[146],"for":[147,159],"mitigating":[148],"stage,":[154],"offering":[155],"new":[157],"paradigm":[158],"bias-aware":[160],"personalization.":[161]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}