{"id":"https://openalex.org/W4412376978","doi":"https://doi.org/10.1145/3726302.3730163","title":"An Alternative to FLOPS Regularization to Effectively Productionize SPLADE-Doc","display_name":"An Alternative to FLOPS Regularization to Effectively Productionize SPLADE-Doc","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412376978","doi":"https://doi.org/10.1145/3726302.3730163"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3730163","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730163","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730163","source":null,"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","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/10.1145/3726302.3730163","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5118969065","display_name":"Aldo Porco","orcid":null},"institutions":[{"id":"https://openalex.org/I1299907687","display_name":"Bloomberg (United States)","ror":"https://ror.org/02rdpzb15","country_code":"US","type":"company","lineage":["https://openalex.org/I1299907687"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Aldo Porco","raw_affiliation_strings":["Bloomberg, New York, NY, USA"],"raw_orcid":"https://orcid.org/0009-0002-7702-0395","affiliations":[{"raw_affiliation_string":"Bloomberg, New York, NY, USA","institution_ids":["https://openalex.org/I1299907687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118969066","display_name":"Dhruv Mehra","orcid":null},"institutions":[{"id":"https://openalex.org/I1299907687","display_name":"Bloomberg (United States)","ror":"https://ror.org/02rdpzb15","country_code":"US","type":"company","lineage":["https://openalex.org/I1299907687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dhruv Mehra","raw_affiliation_strings":["Bloomberg, New York, NY, USA"],"raw_orcid":"https://orcid.org/0009-0005-9920-1754","affiliations":[{"raw_affiliation_string":"Bloomberg, New York, NY, USA","institution_ids":["https://openalex.org/I1299907687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002659016","display_name":"Igor Malioutov","orcid":"https://orcid.org/0000-0002-4058-6638"},"institutions":[{"id":"https://openalex.org/I1299907687","display_name":"Bloomberg (United States)","ror":"https://ror.org/02rdpzb15","country_code":"US","type":"company","lineage":["https://openalex.org/I1299907687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Igor Malioutov","raw_affiliation_strings":["Bloomberg, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-4058-6638","affiliations":[{"raw_affiliation_string":"Bloomberg, New York, NY, USA","institution_ids":["https://openalex.org/I1299907687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004463523","display_name":"Karthik Radhakrishnan","orcid":null},"institutions":[{"id":"https://openalex.org/I1299907687","display_name":"Bloomberg (United States)","ror":"https://ror.org/02rdpzb15","country_code":"US","type":"company","lineage":["https://openalex.org/I1299907687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karthik Radhakrishnan","raw_affiliation_strings":["Bloomberg, New York, NY, USA"],"raw_orcid":"https://orcid.org/0009-0009-0138-6228","affiliations":[{"raw_affiliation_string":"Bloomberg, New York, NY, USA","institution_ids":["https://openalex.org/I1299907687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004644685","display_name":"Moniba Keymanesh","orcid":null},"institutions":[{"id":"https://openalex.org/I1299907687","display_name":"Bloomberg (United States)","ror":"https://ror.org/02rdpzb15","country_code":"US","type":"company","lineage":["https://openalex.org/I1299907687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Moniba Keymanesh","raw_affiliation_strings":["Bloomberg, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-8735-1801","affiliations":[{"raw_affiliation_string":"Bloomberg, New York, NY, USA","institution_ids":["https://openalex.org/I1299907687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086173474","display_name":"Daniel Preo\u021biuc-Pietro","orcid":"https://orcid.org/0000-0002-4504-0212"},"institutions":[{"id":"https://openalex.org/I1299907687","display_name":"Bloomberg (United States)","ror":"https://ror.org/02rdpzb15","country_code":"US","type":"company","lineage":["https://openalex.org/I1299907687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Preo\u0163iuc-Pietro","raw_affiliation_strings":["Bloomberg, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-4504-0212","affiliations":[{"raw_affiliation_string":"Bloomberg, New York, NY, USA","institution_ids":["https://openalex.org/I1299907687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014199889","display_name":"Sean MacAvaney","orcid":"https://orcid.org/0000-0002-8914-2659"},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sean MacAvaney","raw_affiliation_strings":["University of Glasgow, Glasgow, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-8914-2659","affiliations":[{"raw_affiliation_string":"University of Glasgow, Glasgow, United Kingdom","institution_ids":["https://openalex.org/I7882870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088553265","display_name":"Pengxiang Cheng","orcid":"https://orcid.org/0000-0001-5997-705X"},"institutions":[{"id":"https://openalex.org/I1299907687","display_name":"Bloomberg (United States)","ror":"https://ror.org/02rdpzb15","country_code":"US","type":"company","lineage":["https://openalex.org/I1299907687"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pengxiang Cheng","raw_affiliation_strings":["Bloomberg, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-9762-5159","affiliations":[{"raw_affiliation_string":"Bloomberg, New York, NY, USA","institution_ids":["https://openalex.org/I1299907687"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5118969065"],"corresponding_institution_ids":["https://openalex.org/I1299907687"],"apc_list":null,"apc_paid":null,"fwci":4.1903,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.94048107,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2789","last_page":"2793"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9969000220298767,"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"}},"topics":[{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9969000220298767,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9865999817848206,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9645000100135803,"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/flops","display_name":"FLOPS","score":0.7536494135856628},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5583204030990601},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5130097270011902},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2802613377571106},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.18465465307235718}],"concepts":[{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.7536494135856628},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5583204030990601},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5130097270011902},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2802613377571106},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.18465465307235718}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3726302.3730163","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730163","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730163","source":null,"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.gla.ac.uk:352748","is_oa":true,"landing_page_url":"https://eprints.gla.ac.uk/view/author/60888.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4210235606","display_name":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","issn_l":"2622-8912","issn":["2622-8912","2622-8920"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":{"id":"doi:10.1145/3726302.3730163","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730163","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730163","source":null,"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412376978.pdf","grobid_xml":"https://content.openalex.org/works/W4412376978.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1980344365","https://openalex.org/W2114123573","https://openalex.org/W2747329762","https://openalex.org/W3021779606","https://openalex.org/W3099384026","https://openalex.org/W3154280800","https://openalex.org/W3154755316","https://openalex.org/W3155114168","https://openalex.org/W4251372957","https://openalex.org/W4284663260","https://openalex.org/W4284706395","https://openalex.org/W4327499170","https://openalex.org/W4381573351","https://openalex.org/W4384643607","https://openalex.org/W4392846392","https://openalex.org/W4396821195","https://openalex.org/W4400530380","https://openalex.org/W4403577337","https://openalex.org/W6912515347"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4315697128","https://openalex.org/W3102845713","https://openalex.org/W2971502891","https://openalex.org/W3205506801","https://openalex.org/W4280599700","https://openalex.org/W3183570023","https://openalex.org/W4382323155"],"abstract_inverted_index":{"Learned":[0],"Sparse":[1],"Retrieval":[2],"(LSR)":[3],"models":[4],"encode":[5],"text":[6],"as":[7,68,117],"weighted":[8],"term":[9],"vectors,":[10],"which":[11,182],"need":[12],"to":[13,16,32,72],"be":[14],"sparse":[15],"leverage":[17],"inverted":[18],"index":[19],"structures":[20],"during":[21,36],"retrieval.":[22],"SPLADE,":[23],"the":[24,79,98,124,133,144],"most":[25],"popular":[26],"LSR":[27,200],"model,":[28],"uses":[29],"FLOPS":[30,39,90],"regularization":[31,40,95,121],"encourage":[33],"vector":[34],"sparsity":[35,44],"training.":[37],"However,":[38],"does":[41],"not":[42],"ensure":[43],"among":[45],"terms-only":[46],"within":[47],"a":[48,86,157,166],"given":[49],"query":[50],"or":[51],"document.":[52],"Terms":[53],"with":[54,190],"very":[55],"high":[56,82],"Document":[57],"Frequencies":[58],"(DFs)":[59],"substantially":[60],"increase":[61],"latency":[62,152],"in":[63,130,156,169,175,204],"production":[64],"retrieval":[65,109,151,186],"engines,":[66],"such":[67,116],"Apache":[69],"Solr,":[70],"due":[71],"their":[73],"lengthy":[74],"posting":[75,105],"lists.":[76],"To":[77],"address":[78],"issue":[80],"of":[81,89,100,127,146,178],"DFs,":[83],"we":[84,183],"present":[85],"new":[87,94],"variant":[88],"regularization:":[91],"DF-FLOPS.":[92],"This":[93],"technique":[96],"penalizes":[97],"usage":[99],"high-DF":[101,147],"terms,":[102],"thereby":[103],"shortening":[104],"lists":[106],"and":[107,149,171],"reducing":[108],"latency.":[110],"Unlike":[111],"other":[112],"inference-time":[113],"sparsification":[114],"methods,":[115],"stopword":[118],"removal,":[119],"DF-FLOPS":[120,141],"allows":[122],"for":[123,202],"selective":[125],"inclusion":[126],"high-frequency":[128],"terms":[129,134,148],"cases":[131],"where":[132],"are":[135],"truly":[136],"salient.":[137],"We":[138],"find":[139],"that":[140],"successfully":[142],"reduces":[143],"prevalence":[145],"lowers":[150],"(around":[153],"10x":[154],"faster)":[155],"production-grade":[158,205],"engine":[159],"while":[160],"maintaining":[161],"effectiveness":[162],"both":[163],"in-domain":[164],"(only":[165],"2.2-point":[167],"drop":[168],"MRR@10)":[170],"cross-domain":[172],"(improved":[173],"performance":[174],"12":[176],"out":[177],"13":[179],"tasks":[180],"on":[181,188],"tested).":[184],"With":[185],"latencies":[187],"par":[189],"BM25,":[191],"this":[192],"work":[193],"provides":[194],"an":[195],"important":[196],"step":[197],"towards":[198],"making":[199],"practical":[201],"deployment":[203],"search":[206],"engines.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
