{"id":"https://openalex.org/W7164853136","doi":"https://doi.org/10.1145/3805622.3810620","title":"DeHub: Learning Hub-Resistant Representations for Text-Video Retrieval","display_name":"DeHub: Learning Hub-Resistant Representations for Text-Video Retrieval","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164853136","doi":"https://doi.org/10.1145/3805622.3810620"},"language":null,"primary_location":{"id":"doi:10.1145/3805622.3810620","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810620","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805622.3810620","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138672378","display_name":"Anjun Jia","orcid":"https://orcid.org/0009-0000-4816-0941"},"institutions":[{"id":"https://openalex.org/I143413998","display_name":"Qingdao University of Science and Technology","ror":"https://ror.org/041j8js14","country_code":"CN","type":"education","lineage":["https://openalex.org/I143413998"]},{"id":"https://openalex.org/I44468530","display_name":"Qingdao University of Technology","ror":"https://ror.org/01qzc0f54","country_code":"CN","type":"education","lineage":["https://openalex.org/I44468530"]},{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anjun Jia","raw_affiliation_strings":["School of Computer Science and Technology, Qingdao University, Qingdao, Shandong Province, China"],"raw_orcid":"https://orcid.org/0009-0000-4816-0941","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Qingdao University, Qingdao, Shandong Province, China","institution_ids":["https://openalex.org/I80143920","https://openalex.org/I143413998","https://openalex.org/I44468530"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073521712","display_name":"Xiaowei Zhang","orcid":"https://orcid.org/0000-0003-4854-3736"},"institutions":[{"id":"https://openalex.org/I143413998","display_name":"Qingdao University of Science and Technology","ror":"https://ror.org/041j8js14","country_code":"CN","type":"education","lineage":["https://openalex.org/I143413998"]},{"id":"https://openalex.org/I44468530","display_name":"Qingdao University of Technology","ror":"https://ror.org/01qzc0f54","country_code":"CN","type":"education","lineage":["https://openalex.org/I44468530"]},{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Qingdao University, Qingdao, Shandong Province, China"],"raw_orcid":"https://orcid.org/0000-0003-4854-3736","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Qingdao University, Qingdao, Shandong Province, China","institution_ids":["https://openalex.org/I80143920","https://openalex.org/I143413998","https://openalex.org/I44468530"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.93931942,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"186","last_page":"195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8510000109672546,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8510000109672546,"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/T11439","display_name":"Video Analysis and Summarization","score":0.04919999837875366,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.03189999982714653,"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/embedding","display_name":"Embedding","score":0.6456000208854675},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5490999817848206},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5264000296592712},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5205000042915344},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5163000226020813},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4620000123977661},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.45019999146461487},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3944999873638153},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.390500009059906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6654000282287598},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6456000208854675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5669999718666077},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5490999817848206},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5264000296592712},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5205000042915344},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5163000226020813},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4620000123977661},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.45019999146461487},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3944999873638153},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.390500009059906},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3901999890804291},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.3874000012874603},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.37790000438690186},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3483999967575073},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33880001306533813},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.32919999957084656},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.3224000036716461},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.3084000051021576},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27489998936653137},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27140000462532043},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26460000872612},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2603999972343445},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805622.3810620","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810620","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805622.3810620","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810620","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W2078238240","https://openalex.org/W2425121537","https://openalex.org/W2808399042","https://openalex.org/W2963017553","https://openalex.org/W2984006054","https://openalex.org/W2989322838","https://openalex.org/W2997326970","https://openalex.org/W3035376925","https://openalex.org/W3035524453","https://openalex.org/W3043840704","https://openalex.org/W3097580349","https://openalex.org/W3099514962","https://openalex.org/W3153005511","https://openalex.org/W3168433561","https://openalex.org/W3175939205","https://openalex.org/W3204588463","https://openalex.org/W4225414521","https://openalex.org/W4285606530","https://openalex.org/W4304014690","https://openalex.org/W4312372711","https://openalex.org/W4312999114","https://openalex.org/W4313007634","https://openalex.org/W4385767942","https://openalex.org/W4386076265","https://openalex.org/W4389520394","https://openalex.org/W4390871725","https://openalex.org/W4390872434","https://openalex.org/W4390873082","https://openalex.org/W4390874668","https://openalex.org/W4390889802","https://openalex.org/W4402704596","https://openalex.org/W4404782161","https://openalex.org/W4409366779","https://openalex.org/W4413144363","https://openalex.org/W4413144376","https://openalex.org/W4413144844","https://openalex.org/W4413155274","https://openalex.org/W4413259066","https://openalex.org/W4414360309","https://openalex.org/W4417105708","https://openalex.org/W7160123608"],"related_works":[],"abstract_inverted_index":{"Text-video":[0],"retrieval":[1],"has":[2],"achieved":[3],"remarkable":[4],"progress":[5],"through":[6,76],"fine-grained":[7],"cross-modal":[8],"alignment.":[9],"However,":[10],"the":[11,81,127],"hubness":[12,73,109,174],"problem,":[13],"where":[14],"a":[15,28,63,77,84,142],"small":[16],"subset":[17],"of":[18],"samples":[19,115],"disproportionately":[20],"dominate":[21],"nearest-neighbor":[22],"rankings":[23],"for":[24],"many":[25],"queries,":[26],"remains":[27],"fundamental":[29],"obstacle":[30],"in":[31],"high-dimensional":[32],"embedding":[33,103],"spaces.":[34],"Existing":[35],"approaches":[36],"primarily":[37],"rely":[38],"on":[39,159],"post-hoc":[40],"normalization":[41],"during":[42,74],"inference,":[43],"making":[44],"them":[45],"sensitive":[46],"to":[47,93,177],"prior":[48],"data":[49],"distributions":[50,136],"and":[51,101,116,141],"vulnerable":[52],"under":[53,180],"domain":[54],"shift.":[55,182],"To":[56],"address":[57],"this":[58],"limitation,":[59],"we":[60],"propose":[61],"DeHub,":[62],"training-phase":[64,173],"framework":[65],"that":[66,172],"learns":[67],"hub-resistant":[68],"representations":[69],"by":[70],"explicitly":[71],"suppressing":[72],"optimization":[75],"dual-stage":[78],"design.":[79],"In":[80,126],"deterministic":[82],"stage,":[83,129],"Hierarchical":[85],"Subspace":[86],"Decomposition":[87],"(HiSD)":[88],"module":[89],"performs":[90],"in-batch":[91],"PCA":[92],"extract":[94],"latent":[95],"semantic":[96],"subspaces,":[97],"enriching":[98],"representation":[99],"granularity":[100],"reducing":[102],"collapse":[104],"toward":[105],"central":[106],"hubs.":[107,125,156],"A":[108],"weighting":[110],"loss":[111,145],"further":[112],"identifies":[113],"high-centrality":[114],"adaptively":[117],"increases":[118],"their":[119],"contrastive":[120],"penalties,":[121],"mitigating":[122],"semantically":[123,154],"relevant":[124],"probabilistic":[128],"text-video":[130],"pairs":[131],"are":[132],"modeled":[133],"as":[134],"Gaussian":[135],"rather":[137],"than":[138],"fixed":[139],"points,":[140],"boundary":[143],"distance":[144],"enforces":[146],"extremum-based":[147],"separation":[148],"at":[149],"distributional":[150],"boundaries,":[151],"effectively":[152],"repelling":[153],"irrelevant":[155],"Extensive":[157],"experiments":[158],"five":[160],"benchmarks":[161],"demonstrate":[162],"consistent":[163],"improvements":[164],"over":[165],"state-of-the-art":[166],"methods.":[167],"Moreover,":[168],"cross-domain":[169],"evaluations":[170],"confirm":[171],"suppression":[175],"leads":[176],"stronger":[178],"generalization":[179],"distribution":[181]},"counts_by_year":[],"updated_date":"2026-06-16T07:37:23.134862","created_date":"2026-06-16T00:00:00"}