{"id":"https://openalex.org/W4412376981","doi":"https://doi.org/10.1145/3726302.3729946","title":"DePro: Domain Ensemble using Decoupled Prompts for Universal Cross-Domain Retrieval","display_name":"DePro: Domain Ensemble using Decoupled Prompts for Universal Cross-Domain Retrieval","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412376981","doi":"https://doi.org/10.1145/3726302.3729946"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3729946","doi":"https://doi.org/10.1145/3726302.3729946","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729946","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729946","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","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 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729946","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054849720","display_name":"Kaixiang Chen","orcid":"https://orcid.org/0000-0002-8983-6212","observed_orcids":["https://orcid.org/0000-0002-8983-6212","https://orcid.org/0000-0001-6093-951X","https://orcid.org/0000-0002-4061-3683"]},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaixiang Chen","raw_affiliation_strings":["School of Computer Science and Engineering, Southeast University & Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6093-951X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University & Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005651230","display_name":"Pengfei Fang","orcid":"https://orcid.org/0000-0001-8939-0460","observed_orcids":["https://orcid.org/0000-0001-8939-0460"]},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Fang","raw_affiliation_strings":["School of Computer Science and Engineering, Southeast University & Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-8939-0460","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University & Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057436798","display_name":"Hui Xue","orcid":"https://orcid.org/0000-0002-5856-4445","observed_orcids":["https://orcid.org/0000-0002-5856-4445"]},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Xue","raw_affiliation_strings":["School of Computer Science and Engineering, Southeast University & Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-5856-4445","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University & Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":2.011,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.85790582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"958","last_page":"967"},"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":0.5005000233650208,"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":0.5005000233650208,"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":0.36250001192092896,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.07580000162124634,"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/vision-language-models","display_name":"vision-language models","score":0.8429999947547913},{"id":"https://openalex.org/keywords/prompt-tuning","display_name":"prompt tuning","score":0.8679999709129333},{"id":"https://openalex.org/keywords/unseen-domains","display_name":"unseen domains","score":0.718999981880188},{"id":"https://openalex.org/keywords/unseen-classes","display_name":"unseen classes","score":0.871999979019165},{"id":"https://openalex.org/keywords/domain-shift","display_name":"domain shift","score":0.6949999928474426},{"id":"https://openalex.org/keywords/class-shift","display_name":"class shift","score":0.6039999723434448},{"id":"https://openalex.org/keywords/triplet-loss","display_name":"triplet loss","score":0.7509999871253967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7499933242797852},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.7093647122383118},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3443984389305115},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32013410329818726},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09063532948493958},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3726302.3729946","doi":"https://doi.org/10.1145/3726302.3729946","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729946","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729946","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","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 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3726302.3729946","doi":"https://doi.org/10.1145/3726302.3729946","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729946","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729946","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","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 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G4476148956","display_name":null,"funder_award_id":"62476056","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4683334216","display_name":null,"funder_award_id":"62306070","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4685731252","display_name":null,"funder_award_id":"4009002309","funder_id":"https://openalex.org/F4320324856","funder_display_name":"Southeast University"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"},{"id":"https://openalex.org/F4320324856","display_name":"Southeast University","ror":"https://ror.org/04ct4d772"},{"id":"https://openalex.org/F4320334925","display_name":"Science and Technology Support Program of Jiangsu Province","ror":"https://ror.org/02mkqta53"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412376981.pdf","grobid_xml":"https://content.openalex.org/works/W4412376981.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W2039441982","https://openalex.org/W2117539524","https://openalex.org/W2170881581","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2466618734","https://openalex.org/W2471581439","https://openalex.org/W2603445054","https://openalex.org/W2892607309","https://openalex.org/W2963055199","https://openalex.org/W2981720610","https://openalex.org/W3162748909","https://openalex.org/W3175823695","https://openalex.org/W3195007119","https://openalex.org/W3198377975","https://openalex.org/W4225747866","https://openalex.org/W4284687336","https://openalex.org/W4313175608","https://openalex.org/W4319300989","https://openalex.org/W4382458283","https://openalex.org/W4382460786","https://openalex.org/W4382466812","https://openalex.org/W4385764177","https://openalex.org/W4386065763","https://openalex.org/W4386071547","https://openalex.org/W4386075985","https://openalex.org/W4386076063","https://openalex.org/W4386790226","https://openalex.org/W4387969137","https://openalex.org/W4390872773","https://openalex.org/W4393147399","https://openalex.org/W4393252894","https://openalex.org/W4400529146","https://openalex.org/W4400530533","https://openalex.org/W4402727677","https://openalex.org/W4402754025"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"This":[0,162],"paper":[1],"investigates":[2],"the":[3,11,40,52,131,146,153,179,189,212],"potential":[4],"of":[5,13,43,134,152,191],"vision-language":[6],"models":[7],"(VLMs)":[8],"in":[9,58],"addressing":[10],"challenges":[12],"universal":[14,75,99,154],"cross-domain":[15],"retrieval":[16,112,171],"(UCDR),":[17],"where":[18],"queries":[19],"originate":[20],"from":[21,90,145],"unseen":[22,94,217],"domains":[23,95,218],"or":[24,159],"classes.":[25,118],"A":[26],"common":[27],"approach":[28,48],"to":[29,87,105,142,184,198],"adapting":[30],"VLMs":[31],"for":[32],"downstream":[33],"tasks":[34],"involves":[35],"prompt":[36,68],"tuning,":[37],"which":[38],"alleviates":[39],"computational":[41],"burden":[42],"full":[44],"fine-tuning.":[45],"However,":[46],"this":[47],"often":[49],"struggles":[50],"with":[51,150],"domain":[53,76,149,155,167],"and":[54,79,93,116,209,219],"semantic":[55],"shifts":[56],"inherent":[57],"UCDR.":[59],"To":[60,119],"overcome":[61],"these":[62],"limitations,":[63],"we":[64,123,137,177],"propose":[65,178],"a":[66,97,125,139,165],"novel":[67],"decoupling":[69,127],"strategy":[70],"that":[71,129],"separates":[72],"prompts":[73,77,81],"into":[74,96],"(UDPs)":[78],"class":[80,192],"(CPs).":[82],"Specifically,":[83],"UDPs":[84],"are":[85,103],"designed":[86],"unify":[88],"features":[89,144],"both":[91,114],"seen":[92],"cohesive":[98],"domain,":[100],"while":[101],"CPs":[102],"tailored":[104],"capture":[106],"class-specific":[107],"visual":[108],"characteristics,":[109],"enabling":[110],"robust":[111],"across":[113,173,216],"known":[115],"unknown":[117],"ensure":[120],"effective":[121],"decoupling,":[122],"introduce":[124],"dedicated":[126],"loss":[128,141,183],"enforces":[130],"domain-agnostic":[132],"nature":[133],"CPs.":[135],"Additionally,":[136],"employ":[138],"regulation":[140],"align":[143],"frozen":[147],"CLIP":[148],"those":[151],"by":[156,187],"selectively":[157],"integrating":[158],"excluding":[160],"UDPs.":[161],"mechanism":[163],"fosters":[164],"synergistic":[166],"ensemble":[168],"effect,":[169],"enhancing":[170],"generalization":[172,214],"diverse":[174],"domains.":[175],"Finally,":[176],"domain-aware":[180],"triplet-hard":[181],"(DaTri)":[182],"mitigate":[185],"overfitting":[186],"reducing":[188],"risk":[190],"collapse.":[193],"The":[194],"proposed":[195],"framework,":[196],"referred":[197],"as":[199,221],"Domain":[200],"Ensemble":[201],"using":[202],"Decoupled":[203],"Prompts":[204],"(DePro),":[205],"demonstrates":[206],"state-of-the-art":[207],"performance":[208],"effectively":[210],"enhances":[211],"model's":[213],"capacity":[215],"classes,":[220],"validated":[222],"through":[223],"extensive":[224],"experiments.":[225],"Code":[226],"is":[227],"here.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2025-10-10T00:00:00"}