{"id":"https://openalex.org/W7204606906","doi":"https://doi.org/10.18653/2026.emnlp-main.1580","title":"RetrievalRouter: Joint Modality and Architecture Selection for Document Retrieval","display_name":"RetrievalRouter: Joint Modality and Architecture Selection for Document Retrieval","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7204606906","doi":"https://doi.org/10.18653/2026.emnlp-main.1580"},"language":"en","primary_location":{"id":"doi:10.18653/2026.emnlp-main.1580","doi":"https://doi.org/10.18653/2026.emnlp-main.1580","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.1580","pdf_url":"https://aclanthology.org/2026.emnlp-main.1580.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://aclanthology.org/2026.emnlp-main.1580.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062505189","display_name":"Emre Kuru","orcid":"https://orcid.org/0009-0007-6130-6272","observed_orcids":["https://orcid.org/0009-0007-6130-6272"]},"institutions":[{"id":"https://openalex.org/I4210145102","display_name":"Institut Polytechnique de Paris","ror":"https://ror.org/042tfbd02","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I4387153010","display_name":"T\u00e9l\u00e9com SudParis","ror":"https://ror.org/05xvk4r52","country_code":"FR","type":"education","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4387153010"]},{"id":"https://openalex.org/I4405261500","display_name":"Services r\u00e9partis, Architectures, MOd\u00e9lisation, Validation, Administration des R\u00e9seaux","ror":"https://ror.org/05d29yv45","country_code":"FR","type":"facility","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4387153010","https://openalex.org/I4405261500"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Emre Kuru","raw_affiliation_strings":["SAMOVAR , T\u00e9l\u00e9com SudParis , Institut Polytechnique de Paris , Palaiseau , France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SAMOVAR , T\u00e9l\u00e9com SudParis , Institut Polytechnique de Paris , Palaiseau , France","institution_ids":["https://openalex.org/I4210145102","https://openalex.org/I4387153010","https://openalex.org/I4405261500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037609359","display_name":"Mehmet Onur Keskin","orcid":"https://orcid.org/0000-0002-8025-4304","observed_orcids":["https://orcid.org/0000-0002-8025-4304"]},"institutions":[{"id":"https://openalex.org/I44925452","display_name":"\u00d6zye\u011fin University","ror":"https://ror.org/01jjhfr75","country_code":"TR","type":"education","lineage":["https://openalex.org/I44925452"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Mehmet Onur Keskin","raw_affiliation_strings":["\u00d6zyegin University , Istanbul , T\u00fcrkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u00d6zyegin University , Istanbul , T\u00fcrkiye","institution_ids":["https://openalex.org/I44925452"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014176390","display_name":"Reza Farahbakhsh","orcid":"https://orcid.org/0000-0003-3219-3700","observed_orcids":["https://orcid.org/0000-0003-3219-3700"]},"institutions":[{"id":"https://openalex.org/I4210145102","display_name":"Institut Polytechnique de Paris","ror":"https://ror.org/042tfbd02","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I4387153010","display_name":"T\u00e9l\u00e9com SudParis","ror":"https://ror.org/05xvk4r52","country_code":"FR","type":"education","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4387153010"]},{"id":"https://openalex.org/I4405261500","display_name":"Services r\u00e9partis, Architectures, MOd\u00e9lisation, Validation, Administration des R\u00e9seaux","ror":"https://ror.org/05d29yv45","country_code":"FR","type":"facility","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4387153010","https://openalex.org/I4405261500"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Reza Farahbakhsh","raw_affiliation_strings":["SAMOVAR , T\u00e9l\u00e9com SudParis , Institut Polytechnique de Paris , Palaiseau , France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SAMOVAR , T\u00e9l\u00e9com SudParis , Institut Polytechnique de Paris , Palaiseau , France","institution_ids":["https://openalex.org/I4210145102","https://openalex.org/I4387153010","https://openalex.org/I4405261500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107205316","display_name":"No\u00ebl Crespi","orcid":"https://orcid.org/0000-0003-2962-192X","observed_orcids":["https://orcid.org/0000-0003-2962-192X"]},"institutions":[{"id":"https://openalex.org/I4210145102","display_name":"Institut Polytechnique de Paris","ror":"https://ror.org/042tfbd02","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I4387153010","display_name":"T\u00e9l\u00e9com SudParis","ror":"https://ror.org/05xvk4r52","country_code":"FR","type":"education","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4387153010"]},{"id":"https://openalex.org/I4405261500","display_name":"Services r\u00e9partis, Architectures, MOd\u00e9lisation, Validation, Administration des R\u00e9seaux","ror":"https://ror.org/05d29yv45","country_code":"FR","type":"facility","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4387153010","https://openalex.org/I4405261500"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Noel Crespi","raw_affiliation_strings":["SAMOVAR , T\u00e9l\u00e9com SudParis , Institut Polytechnique de Paris , Palaiseau , France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SAMOVAR , T\u00e9l\u00e9com SudParis , Institut Polytechnique de Paris , Palaiseau , France","institution_ids":["https://openalex.org/I4210145102","https://openalex.org/I4387153010","https://openalex.org/I4405261500"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"35968","last_page":"35982"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9872999787330627,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9872999787330627,"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/T10028","display_name":"Topic Modeling","score":0.008899999782443047,"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":0.0007999999797903001,"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/document-retrieval","display_name":"document retrieval","score":0.9259999990463257},{"id":"https://openalex.org/keywords/accuracy-latency-trade-off","display_name":"accuracy-latency trade-off","score":0.7099999785423279},{"id":"https://openalex.org/keywords/dense-retrieval","display_name":"dense retrieval","score":0.6859999895095825},{"id":"https://openalex.org/keywords/multimodal-retrieval","display_name":"multimodal retrieval","score":0.9409999847412109},{"id":"https://openalex.org/keywords/retrieval-latency","display_name":"retrieval latency","score":0.5}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8230000138282776},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6202999949455261},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5454000234603882},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.5069000124931335},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4862000048160553},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4821000099182129},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.46470001339912415},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4250999987125397},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3824999928474426},{"id":"https://openalex.org/C551230270","wikidata":"https://www.wikidata.org/wiki/Q4368942","display_name":"Data retrieval","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.34130001068115234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29789999127388},{"id":"https://openalex.org/C2775896111","wikidata":"https://www.wikidata.org/wiki/Q642560","display_name":"Router","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C47487241","wikidata":"https://www.wikidata.org/wiki/Q5227230","display_name":"Data access","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2700999975204468},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/2026.emnlp-main.1580","doi":"https://doi.org/10.18653/2026.emnlp-main.1580","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.1580","pdf_url":"https://aclanthology.org/2026.emnlp-main.1580.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2608.25625","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.25625","pdf_url":"https://arxiv.org/pdf/2608.25625","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:hal-05730181v1","doi":null,"is_oa":true,"landing_page_url":"https://hal.science/hal-05730181v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"The 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP), Oct 2026, Budapest, Hungary","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.18653/2026.emnlp-main.1580","doi":"https://doi.org/10.18653/2026.emnlp-main.1580","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.1580","pdf_url":"https://aclanthology.org/2026.emnlp-main.1580.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204606906.pdf","grobid_xml":"https://content.openalex.org/works/W7204606906.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W2909544278","https://openalex.org/W4353007118","https://openalex.org/W4385574177","https://openalex.org/W4390041933","https://openalex.org/W4391709255","https://openalex.org/W4400373146","https://openalex.org/W4403578420","https://openalex.org/W4404341467","https://openalex.org/W4404782721","https://openalex.org/W4414939355","https://openalex.org/W4415038033","https://openalex.org/W4415110444","https://openalex.org/W4416035344","https://openalex.org/W7101786138","https://openalex.org/W7116059159"],"related_works":["https://openalex.org/W7219129507","https://openalex.org/W7197023394","https://openalex.org/W7212935079","https://openalex.org/W7151512353","https://openalex.org/W7124458051","https://openalex.org/W7154751765","https://openalex.org/W7162545024","https://openalex.org/W7165689667","https://openalex.org/W7155502819","https://openalex.org/W7155774608"],"abstract_inverted_index":{"Document":[0],"retrieval":[1,12,23,113],"increasingly":[2],"supports":[3],"highstakes":[4],"information":[5],"access":[6],"in":[7,16,22,182],"finance,":[8],"healthcare,":[9],"and":[10,21,40,62,92,127,142,153,180],"law.Modern":[11],"pipelines":[13,36],"vary":[14],"both":[15,178],"modality":[17],"(text":[18],"or":[19,26,173],"multimodal)":[20],"architecture":[24],"(dense":[25],"late-interaction).These":[27],"choices":[28],"impose":[29],"a":[30,101],"hard":[31],"compromise:":[32],"the":[33,47,74,86,108,123,144],"most":[34],"effective":[35],"are":[37],"too":[38],"slow":[39],"expensive":[41],"to":[42,50],"run":[43],"at":[44,73],"scale,":[45],"while":[46,171],"fastest":[48],"fail":[49],"retrieve":[51],"evidence":[52,61],"from":[53,107],"complex":[54],"documents.Practitioners":[55],"must":[56],"therefore":[57],"choose":[58],"between":[59],"missed":[60],"unusable":[63],"latency,":[64],"with":[65,157],"no":[66,95],"principled":[67],"basis":[68],"for":[69,128],"adapting":[70],"that":[71,78,105,137],"choice":[72],"query":[75,84,109],"level.We":[76],"show":[77],"this":[79],"compromise":[80],"is":[81,138,149],"unnecessary.Not":[82],"every":[83,129],"requires":[85],"same":[87],"pipeline.Across":[88],"benchmarks":[89],"spanning":[90],"financial":[91],"scientific":[93],"corpora,":[94],"static":[96,130,146],"pipeline":[97,114],"dominates.We":[98],"introduce":[99],"RetrievalRouter,":[100],"lightweight":[102],"query-aware":[103],"router":[104],"learns,":[106],"text":[110],"alone,":[111],"which":[112],"best":[115,145],"fits":[116],"each":[117],"query.A":[118],"single":[119],"tunable":[120],"parameter":[121],"exposes":[122],"full":[124],"accuracy-latency":[125],"frontier,":[126],"baseline,":[131,147],"RetrievalRouter":[132,148,163],"offers":[133],"an":[134],"operating":[135],"point":[136],"simultaneously":[139],"more":[140,151],"accurate":[141,152],"faster.Against":[143],"2.5%":[150],"12.4\u00d7":[154],"faster.Furthermore,":[155],"compared":[156],"prior":[158],"adaptive":[159],"strategy":[160],"selection":[161],"methods,":[162],"achieves":[164],"significantly":[165],"higher":[166],"nDCG@5":[167,179],"across":[168],"accuracy-oriented":[169],"settings,":[170],"matching":[172],"numerically":[174],"outperforming":[175],"them":[176],"on":[177],"latency":[181],"latencyoriented":[183],"settings.Our":[184],"code:":[185],"https://github.":[186],"com/emrekuruu/retrieval-router":[187]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-08-29T00:00:00"}
