{"id":"https://openalex.org/W7147290527","doi":"https://doi.org/10.48550/arxiv.2603.27556","title":"Towards Domain-Generalized Open-Vocabulary Object Detection: A Progressive Domain-invariant Cross-modal Alignment Method","display_name":"Towards Domain-Generalized Open-Vocabulary Object Detection: A Progressive Domain-invariant Cross-modal Alignment Method","publication_year":2026,"publication_date":"2026-03-29","ids":{"openalex":"https://openalex.org/W7147290527","doi":"https://doi.org/10.48550/arxiv.2603.27556"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.27556","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27556","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.27556","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100555426","display_name":"Xiaoran Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Xiaoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132564887","display_name":"Xiaoshan Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Xiaoshan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101738255","display_name":"Jiangang Yang","orcid":"https://orcid.org/0000-0002-0464-8336"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Jiangang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132562590","display_name":"Yifan Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Yifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132632508","display_name":"Jian K. Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132544145","display_name":"Changsheng Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Changsheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.7718999981880188,"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":0.7718999981880188,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.11590000241994858,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0357000008225441,"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/ambiguity","display_name":"Ambiguity","score":0.5885999798774719},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5817999839782715},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.4138000011444092},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.3919999897480011},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3849000036716461},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.38089999556541443},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.3630000054836273},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.3492000102996826}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7045000195503235},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6563000082969666},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.5885999798774719},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5817999839782715},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4571000039577484},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.4138000011444092},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3919999897480011},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3630000054836273},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.3239000141620636},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28119999170303345},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2648000121116638},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C62799726","wikidata":"https://www.wikidata.org/wiki/Q190056","display_name":"Hilbert space","level":2,"score":0.25099998712539673},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.27556","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27556","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.27556","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27556","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7509388327598572}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Open-Vocabulary":[0,59],"Object":[1,60],"Detection":[2,61],"(OVOD)":[3],"has":[4],"achieved":[5],"remarkable":[6],"success":[7,15],"in":[8],"generalizing":[9],"to":[10,132,144,150],"novel":[11,86],"categories.":[12],"However,":[13],"this":[14,26],"often":[16],"rests":[17],"on":[18,170],"the":[19,34,41,81,151,154],"implicit":[20],"assumption":[21],"of":[22,33,80,153],"domain":[23,145],"stationarity.":[24],"In":[25],"work,":[27],"we":[28,66,99],"provide":[29],"a":[30,38,78,113,163,167],"principled":[31],"revisit":[32],"OVOD":[35],"paradigm,":[36],"uncovering":[37],"fundamental":[39],"vulnerability:":[40],"fragile":[42],"coupling":[43],"between":[44],"visual":[45,69,88,130],"manifolds":[46],"and":[47,116,129,166],"textual":[48],"embeddings":[49],"when":[50],"distribution":[51],"shifts":[52,70,146],"occur.":[53],"We":[54],"first":[55],"systematically":[56],"formalize":[57],"Domain-Generalized":[58],"(DG-OVOD).":[62],"Through":[63],"empirical":[64],"analysis,":[65],"demonstrate":[67],"that":[68,141,176],"do":[71],"not":[72],"merely":[73],"add":[74],"noise;":[75],"they":[76],"cause":[77],"collapse":[79],"latent":[82,155],"cross-modal":[83,156],"space":[84],"where":[85],"category":[87],"signals":[89],"detach":[90],"from":[91,108],"their":[92],"semantic":[93],"anchors.":[94],"Motivated":[95],"by":[96,111],"these":[97],"insights,":[98],"propose":[100],"Progressive":[101],"Domain-invariant":[102],"Cross-modal":[103],"Alignment":[104],"(PICA).":[105],"PICA":[106],"departs":[107],"uniform":[109],"training":[110],"introducing":[112],"multi-level":[114],"ambiguity":[115],"signal":[117],"strength":[118],"curriculum.":[119],"It":[120],"builds":[121],"adaptive":[122],"pseudo-word":[123],"prototypes,":[124],"refined":[125],"via":[126],"sample":[127],"confidence":[128],"consistency,":[131],"enforce":[133],"invariant":[134],"cross-domain":[135],"modality":[136],"alignment.":[137],"Our":[138,159],"findings":[139],"suggest":[140],"OVOD's":[142],"robustness":[143],"is":[147],"intrinsically":[148],"linked":[149],"stability":[152],"alignment":[157],"space.":[158],"work":[160],"provides":[161],"both":[162],"challenging":[164],"benchmark":[165],"new":[168],"perspective":[169],"building":[171],"truly":[172],"generalizable":[173],"open-vocabulary":[174],"systems":[175],"extend":[177],"beyond":[178],"static":[179],"laboratory":[180],"conditions.":[181]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-02T00:00:00"}