{"id":"https://openalex.org/W7162646997","doi":"https://doi.org/10.48550/arxiv.2605.28444","title":"Bilinear Coordinate Alignment for Training-Free Task-Vector Transfer","display_name":"Bilinear Coordinate Alignment for Training-Free Task-Vector Transfer","publication_year":2026,"publication_date":"2026-05-27","ids":{"openalex":"https://openalex.org/W7162646997","doi":"https://doi.org/10.48550/arxiv.2605.28444"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.28444","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28444","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.2605.28444","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022099313","display_name":"\uc190\uc911\uc6a9","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Son, Jungyong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137220792","display_name":"Jinwook Jung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jung, Jinwook","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137225080","display_name":"Minhee Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Minhee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5048206537","display_name":"Sungyong Baik","orcid":"https://orcid.org/0000-0001-5702-4618"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baik, Sungyong","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.49570000171661377,"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":0.49570000171661377,"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":0.17520000040531158,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.03150000050663948,"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/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.8270999789237976},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6366000175476074},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.49559998512268066},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.44999998807907104},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.42989999055862427},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.421099990606308},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.29170000553131104}],"concepts":[{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.8270999789237976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6741999983787537},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6366000175476074},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.49559998512268066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45089998841285706},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.44999998807907104},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.42989999055862427},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42419999837875366},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.421099990606308},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.41519999504089355},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29170000553131104},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2831000089645386},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2587999999523163},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.28444","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28444","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.2605.28444","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28444","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":0.4616435468196869}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Fine-tuning":[0],"large-scale":[1],"pre-trained":[2,23],"models":[3,82,207],"is":[4,37],"a":[5,18,22,65,88,110,115,151,158,178,183],"recent":[6,54],"prevalent":[7],"paradigm":[8],"for":[9,161],"adapting":[10],"general":[11],"representations":[12],"to":[13,39,72,94],"specialized":[14],"tasks.":[15],"However,":[16],"when":[17],"new":[19],"version":[20],"of":[21,42,108,122],"model":[24,67],"becomes":[25],"available,":[26],"expertise":[27,74],"acquired":[28],"through":[29,165],"fine-tuning":[30],"cannot":[31],"be":[32,130],"directly":[33],"reused":[34],"because":[35],"it":[36],"tied":[38],"the":[40,43,61,120],"parameterization":[41],"original":[44],"model,":[45,71],"requiring":[46],"another":[47],"costly":[48],"fine-tuning.":[49],"To":[50],"address":[51],"this":[52,105,144],"inefficiency,":[53],"work":[55],"uses":[56],"task":[57,111,123,163],"vectors,":[58],"defined":[59],"as":[60,114,132,150],"parameter":[62,116,189],"difference":[63],"between":[64,136],"fine-tuned":[66],"and":[68,125,139,155,195,213],"its":[69],"base":[70],"transfer":[73,149,204],"across":[75,206],"models.":[76],"While":[77],"existing":[78,203],"methods":[79,205],"bridge":[80],"disparate":[81],"by":[83,143],"matching":[84],"activations":[85,138],"or":[86],"gradients,":[87],"significant":[89],"performance":[90],"gap":[91],"remains":[92],"relative":[93],"direct":[95],"fine-tuning,":[96],"suggesting":[97],"that":[98,127,208],"these":[99],"partial":[100],"correspondences":[101],"are":[102],"insufficient.":[103],"In":[104],"work,":[106],"instead":[107],"viewing":[109],"vector":[112],"merely":[113],"offset,":[117],"we":[118,146],"revisit":[119],"formation":[121],"vectors":[124,164],"show":[126],"they":[128],"can":[129],"derived":[131],"accumulated":[133],"bilinear":[134],"interactions":[135],"input-side":[137],"output-side":[140],"gradients.":[141],"Motivated":[142],"observation,":[145],"formulate":[147],"task-vector":[148],"dual-space":[152],"alignment":[153],"problem":[154],"propose":[156],"BiCo,":[157],"training-free":[159],"framework":[160],"transferring":[162],"Bilinear":[166],"Coordinate":[167],"alignment.":[168],"BiCo":[169,200],"estimates":[170],"orthogonal":[171],"Procrustes":[172],"mappings":[173],"in":[174,210],"both":[175],"spaces":[176],"using":[177],"single":[179],"forward-backward":[180],"pass":[181],"on":[182],"small":[184],"calibration":[185],"set,":[186],"without":[187],"any":[188],"update.":[190],"Across":[191],"extensive":[192],"computer":[193],"vision":[194],"natural":[196],"language":[197],"processing":[198],"benchmarks,":[199],"consistently":[201],"outperforms":[202],"differ":[209],"width,":[211],"depth,":[212],"pre-training":[214],"configuration.":[215]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-29T00:00:00"}