{"id":"https://openalex.org/W4414360309","doi":"https://doi.org/10.24963/ijcai.2025/643","title":"DUQ: Dual Uncertainty Quantification for Text-Video Retrieval","display_name":"DUQ: Dual Uncertainty Quantification for Text-Video Retrieval","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414360309","doi":"https://doi.org/10.24963/ijcai.2025/643"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/643","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/643","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015367941","display_name":"Xin Liu","orcid":"https://orcid.org/0000-0003-4090-1703"},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Liu","raw_affiliation_strings":["Southwestern University of Finance and Economics"],"affiliations":[{"raw_affiliation_string":"Southwestern University of Finance and Economics","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101320971","display_name":"Shibai Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shibai Yin","raw_affiliation_strings":["Southwestern University of Finance and Economics"],"affiliations":[{"raw_affiliation_string":"Southwestern University of Finance and Economics","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384838","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-9515-076X"},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["Southwestern University of Finance and Economics"],"affiliations":[{"raw_affiliation_string":"Southwestern University of Finance and Economics","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101518774","display_name":"Jiaxin Zhu","orcid":"https://orcid.org/0000-0002-0905-2355"},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxin Zhu","raw_affiliation_strings":["Southwestern University of Finance and Economics"],"affiliations":[{"raw_affiliation_string":"Southwestern University of Finance and Economics","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047378516","display_name":"Xingyang Wang","orcid":"https://orcid.org/0009-0005-1843-1268"},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingyang Wang","raw_affiliation_strings":["Southwestern University of Finance and Economics"],"affiliations":[{"raw_affiliation_string":"Southwestern University of Finance and Economics","institution_ids":["https://openalex.org/I204831749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113658858","display_name":"Yee-Hong Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yee-Hong Yang","raw_affiliation_strings":["University of Alberta"],"affiliations":[{"raw_affiliation_string":"University of Alberta","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5015367941"],"corresponding_institution_ids":["https://openalex.org/I204831749"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1399278,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5779","last_page":"5787"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9717000126838684,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9717000126838684,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9603999853134155,"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":0.944100022315979,"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/similarity","display_name":"Similarity (geometry)","score":0.6729000210762024},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.6211000084877014},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5866000056266785},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5827999711036682},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5006999969482422},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48249998688697815},{"id":"https://openalex.org/keywords/uncertainty-reduction-theory","display_name":"Uncertainty reduction theory","score":0.462799996137619},{"id":"https://openalex.org/keywords/video-retrieval","display_name":"Video retrieval","score":0.46140000224113464},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.430400013923645}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7267000079154968},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6729000210762024},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6211000084877014},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5866000056266785},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5827999711036682},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5823000073432922},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5006999969482422},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48249998688697815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47600001096725464},{"id":"https://openalex.org/C94361409","wikidata":"https://www.wikidata.org/wiki/Q7882500","display_name":"Uncertainty reduction theory","level":2,"score":0.462799996137619},{"id":"https://openalex.org/C2983174267","wikidata":"https://www.wikidata.org/wiki/Q3775098","display_name":"Video retrieval","level":2,"score":0.46140000224113464},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.430400013923645},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.38119998574256897},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.37630000710487366},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3666999936103821},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.36559998989105225},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36090001463890076},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.358599990606308},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3305000066757202},{"id":"https://openalex.org/C149189445","wikidata":"https://www.wikidata.org/wiki/Q5283894","display_name":"Divergence-from-randomness model","level":3,"score":0.32580000162124634},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.2703999876976013},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/643","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/643","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"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":{"Text-video":[0],"retrieval":[1,150],"establishes":[2],"accurate":[3],"similarity":[4,20,81,129],"relationships":[5],"between":[6,116,130],"text":[7,39],"and":[8,13,25,69,89,146],"video":[9,36,45],"through":[10],"feature":[11],"enhancement":[12],"granularity":[14],"alignment.":[15],"However,":[16],"relying":[17],"solely":[18],"on":[19,136],"to":[21,73,84,105],"associate":[22],"intra-pair":[23,67,75,80],"features":[24,28],"distinguish":[26],"inter-pair":[27,70,96,101],"is":[29],"insufficient,":[30],"\\textit{e.g.},":[31],"when":[32],"querying":[33],"a":[34,55,107],"multi-scene":[35],"with":[37],"sparse":[38],"or":[40],"selecting":[41],"the":[42,114,126],"most":[43],"relevant":[44],"from":[46],"many":[47],"similar":[48,117],"candidates.":[49],"In":[50],"this":[51,92],"paper,":[52],"we":[53,77,98],"propose":[54,78,99],"novel":[56],"Dual":[57],"Uncertainty":[58],"Quantification":[59],"(DUQ)":[60],"model":[61,91,135],"that":[62],"separately":[63],"handles":[64],"uncertainties":[65],"in":[66],"interaction":[68],"exclusion.":[71],"Specifically,":[72],"enhance":[74],"interaction,":[76],"an":[79,100],"uncertainty":[82,103],"module":[83,104],"provide":[85],"similarity-based":[86],"trustworthy":[87],"predictions":[88],"explicitly":[90],"uncertainty.":[93],"To":[94],"increase":[95],"exclusion,":[97],"distance":[102],"construct":[106],"distance-based":[108],"diversity":[109],"probability":[110],"embeding,":[111],"thereby":[112],"widening":[113],"gap":[115],"features.":[118,131],"The":[119],"two":[120],"components":[121],"work":[122],"synergistically,":[123],"jointly":[124],"improving":[125],"calculation":[127],"of":[128],"We":[132],"evaluate":[133],"our":[134],"six":[137],"benchmark":[138],"datasets:":[139],"MSRVTT":[140],"(51.2%),":[141],"DiDeMo,":[142],"MSVD,":[143],"LSMDC,":[144],"Charades,":[145],"VATEX,":[147],"achieving":[148],"state-of-the-art":[149],"performance.":[151]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
