{"id":"https://openalex.org/W7131857488","doi":"https://doi.org/10.48550/arxiv.2602.22547","title":"Towards Dynamic Dense Retrieval with Routing Strategy","display_name":"Towards Dynamic Dense Retrieval with Routing Strategy","publication_year":2026,"publication_date":"2026-02-26","ids":{"openalex":"https://openalex.org/W7131857488","doi":"https://doi.org/10.48550/arxiv.2602.22547"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.22547","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.22547","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.22547","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127451149","display_name":"Zhan Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Su, Zhan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5097357444","display_name":"Fengran Mo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mo, Fengran","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127437606","display_name":"Jinghan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jinghan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103129849","display_name":"Yuchen Hui","orcid":"https://orcid.org/0000-0002-9659-3714"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hui, Yuchen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123118762","display_name":"Jia Ao Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Jia Ao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127260074","display_name":"Bingbing Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Bingbing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127176699","display_name":"Jian-Yun Nie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie, Jian-Yun","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5127451149"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.2718999981880188,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.2718999981880188,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.2337999939918518,"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":0.07919999957084656,"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/domain","display_name":"Domain (mathematical analysis)","score":0.5903000235557556},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.4799000024795532},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.47940000891685486},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.42640000581741333},{"id":"https://openalex.org/keywords/scratch","display_name":"Scratch","score":0.2939000129699707},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.29260000586509705}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8474000096321106},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5903000235557556},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.4799000024795532},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.47940000891685486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45249998569488525},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.42640000581741333},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.36230000853538513},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33809998631477356},{"id":"https://openalex.org/C2781235140","wikidata":"https://www.wikidata.org/wiki/Q275131","display_name":"Scratch","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2831000089645386},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2775000035762787},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C551230270","wikidata":"https://www.wikidata.org/wiki/Q4368942","display_name":"Data retrieval","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.22547","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.22547","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.22547","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.22547","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"\\textit{de":[1],"facto}":[2],"paradigm":[3,23,81],"for":[4,17,70,109,175],"applying":[5,176],"dense":[6,93,98,163,177],"retrieval":[7,94,132,164,178],"(DR)":[8],"to":[9,35,67,76,159,179],"new":[10,37],"tasks":[11,140],"involves":[12],"fine-tuning":[13],"a":[14,18,36,91,106,110,121,171],"pre-trained":[15],"model":[16,74],"specific":[19,111],"task.":[20],"However,":[21],"this":[22,80,143],"has":[24],"two":[25],"significant":[26],"limitations:":[27],"(1)":[28],"It":[29],"is":[30,43,82],"difficult":[31],"adapt":[32],"the":[33,40,61,73,131,153,157],"DR":[34,47,147],"domain":[38,128],"if":[39],"training":[41,154],"dataset":[42],"limited.":[44],"(2)":[45],"Old":[46],"models":[48,54],"are":[49,56,63],"simply":[50],"replaced":[51],"by":[52],"newer":[53],"that":[55,142],"trained":[57],"from":[58],"scratch":[59],"when":[60],"former":[62],"no":[64],"longer":[65],"up":[66],"date.":[68],"Especially":[69],"scenarios":[71],"where":[72],"needs":[75],"be":[77,117],"updated":[78],"frequently,":[79],"prohibitively":[83],"expensive.":[84],"To":[85],"address":[86],"these":[87],"challenges,":[88],"we":[89],"propose":[90],"novel":[92],"approach,":[95],"termed":[96],"\\textit{dynamic":[97],"retrieval}":[99],"(DDR).":[100],"DDR":[101],"uses":[102],"\\textit{prefix":[103],"tuning}":[104],"as":[105,170],"\\textit{module}":[107],"specialized":[108],"domain.":[112],"These":[113],"modules":[114],"can":[115,145],"then":[116],"compositional":[118],"combined":[119],"with":[120],"dynamic":[122],"routing":[123],"strategy,":[124],"enabling":[125],"highly":[126],"flexible":[127,162],"adaptation":[129],"in":[130,165],"part.":[133],"Extensive":[134],"evaluation":[135],"on":[136],"six":[137],"zero-shot":[138],"downstream":[139],"demonstrates":[141],"approach":[144],"surpass":[146],"while":[148],"utilizing":[149],"only":[150],"2\\%":[151],"of":[152],"parameters,":[155],"paving":[156],"way":[158],"achieve":[160],"more":[161],"IR.":[166],"We":[167],"see":[168],"it":[169],"promising":[172],"future":[173],"direction":[174],"various":[180],"tasks.":[181]},"counts_by_year":[],"updated_date":"2026-02-28T06:18:59.386488","created_date":"2026-02-28T00:00:00"}