{"id":"https://openalex.org/W7125744499","doi":"https://doi.org/10.48550/arxiv.2601.16582","title":"X-Aligner: Composed Visual Retrieval without the Bells and Whistles","display_name":"X-Aligner: Composed Visual Retrieval without the Bells and Whistles","publication_year":2026,"publication_date":"2026-01-23","ids":{"openalex":"https://openalex.org/W7125744499","doi":"https://doi.org/10.48550/arxiv.2601.16582"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.16582","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.16582","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.16582","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123853197","display_name":"Yuqian Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zheng, Yuqian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065862728","display_name":"Mariana-Iuliana Georgescu","orcid":"https://orcid.org/0000-0001-8277-1340"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Georgescu, Mariana-Iuliana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5123853197"],"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":0.9772999882698059,"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":0.9772999882698059,"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":0.014999999664723873,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.0008999999845400453,"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/encoder","display_name":"Encoder","score":0.6843000054359436},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.6697999835014343},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5425999760627747},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5002999901771545},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.4569000005722046},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34450000524520874},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.3246000111103058}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7919999957084656},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6843000054359436},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.6697999835014343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5839999914169312},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5425999760627747},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5002999901771545},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4569000005722046},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39739999175071716},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3450999855995178},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.3246000111103058},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.29989999532699585},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.29789999127388},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2888999879360199},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.2630999982357025},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.16582","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.16582","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.16582","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.16582","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":"article"},"sustainable_development_goals":[{"score":0.5161216855049133,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Composed":[0,172],"Video":[1],"Retrieval":[2,174],"(CoVR)":[3],"facilitates":[4],"video":[5],"retrieval":[6],"by":[7],"combining":[8],"visual":[9,66,96],"and":[10,67,70,149,151,179,195],"textual":[11,68,132],"queries.":[12],"However,":[13],"existing":[14],"CoVR":[15,39,187],"frameworks":[16],"typically":[17],"fuse":[18,65],"multimodal":[19,73,88],"inputs":[20,69],"in":[21,106,127],"a":[22,37,54,189],"single":[23],"stage,":[24,118,130],"achieving":[25],"only":[26,119],"marginal":[27],"gains":[28],"over":[29],"initial":[30],"baseline.":[31],"To":[32,81],"address":[33],"this,":[34],"we":[35,90,166],"propose":[36],"novel":[38,55],"framework":[40,52,103,141,182],"that":[41,63,76],"leverages":[42],"the":[43,78,84,87,92,95,111,116,120,128,131,155,171],"representational":[44],"power":[45],"of":[46,60,77,86,94,144,191],"Vision":[47],"Language":[48],"Models":[49],"(VLMs).":[50],"Our":[51,181],"incorporates":[53],"cross-attention":[56,61],"module":[57,123],"X-Aligner,":[58],"composed":[59],"layers":[62],"progressively":[64],"align":[71],"their":[72],"representation":[74,85],"with":[75],"target":[79],"video.":[80],"further":[82],"enhance":[83],"query,":[89],"incorporate":[91],"caption":[93],"query":[97,133],"as":[98],"an":[99],"additional":[100],"input.":[101],"The":[102],"is":[104,124,135],"trained":[105],"two":[107],"stages":[108],"to":[109,161],"preserve":[110],"pretrained":[112],"VLM":[113],"representation.":[114],"In":[115,159],"first":[117],"newly":[121],"introduced":[122],"trained,":[125],"while":[126],"second":[129],"encoder":[134],"also":[136],"fine-tuned.":[137],"We":[138],"implement":[139],"our":[140],"on":[142,154,164,170,186,193,200],"top":[143],"BLIP-family":[145],"architecture,":[146],"namely":[147],"BLIP":[148],"BLIP-2,":[150],"train":[152],"it":[153],"Webvid-CoVR":[156],"data":[157,176],"set.":[158],"addition":[160],"in-domain":[162],"evaluation":[163],"Webvid-CoVR-Test,":[165,194],"perform":[167],"zero-shot":[168,198],"evaluations":[169],"Image":[173],"(CIR)":[175],"sets":[177],"CIRCO":[178],"Fashion-IQ.":[180],"achieves":[183],"state-of-the-art":[184],"performance":[185],"obtaining":[188],"Recall@1":[190],"63.93%":[192],"demonstrates":[196],"strong":[197],"generalization":[199],"CIR":[201],"tasks.":[202]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-01-27T00:00:00"}