{"id":"https://openalex.org/W7162318594","doi":"https://doi.org/10.48550/arxiv.2605.23028","title":"RADAR: Relative Angular Divergence Across Representations","display_name":"RADAR: Relative Angular Divergence Across Representations","publication_year":2026,"publication_date":"2026-05-21","ids":{"openalex":"https://openalex.org/W7162318594","doi":"https://doi.org/10.48550/arxiv.2605.23028"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.23028","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23028","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.2605.23028","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120688486","display_name":"Xavier Cadet","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cadet, Xavier","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136922493","display_name":"Mateusz Nowak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nowak, Mateusz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136937918","display_name":"Peter Chin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chin, Peter","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":0.3197999894618988,"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":0.3197999894618988,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.0966000035405159,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.08990000188350677,"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/metric","display_name":"Metric (unit)","score":0.6873000264167786},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6707000136375427},{"id":"https://openalex.org/keywords/transferability","display_name":"Transferability","score":0.6079000234603882},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.574999988079071},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5257999897003174},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4966999888420105},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.42399999499320984},{"id":"https://openalex.org/keywords/displacement","display_name":"Displacement (psychology)","score":0.4196000099182129},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.3797000050544739},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3271999955177307}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6873000264167786},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6707000136375427},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.6079000234603882},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.574999988079071},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5562999844551086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.539900004863739},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5257999897003174},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4966999888420105},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46149998903274536},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.42399999499320984},{"id":"https://openalex.org/C107551265","wikidata":"https://www.wikidata.org/wiki/Q1458245","display_name":"Displacement (psychology)","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3797000050544739},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3686999976634979},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3391000032424927},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.32120001316070557},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C108439606","wikidata":"https://www.wikidata.org/wiki/Q3305038","display_name":"Angular displacement","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2906000018119812},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.2727999985218048},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26809999346733093},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.23028","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23028","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.2605.23028","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23028","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Machine":[0],"learning":[1],"methods":[2],"rely":[3],"on":[4,153,182],"data.":[5],"However,":[6],"gathering":[7],"suitable":[8],"data":[9],"can":[10,46],"be":[11],"challenging":[12],"due":[13],"to":[14,33,49,110,149],"availability":[15],"constraints,":[16],"cost,":[17],"or":[18,168],"the":[19,75,111,119,176,183,186],"need":[20],"for":[21,66],"domain":[22,106,164],"expertise.":[23],"Expanding":[24],"datasets":[25],"with":[26,128,136,159,191],"additional":[27],"sources":[28],"is":[29,108],"a":[30,50,61],"common":[31],"response":[32],"limited":[34],"data,":[35],"yet":[36],"this":[37],"practice":[38],"does":[39],"not":[40],"always":[41],"improve":[42],"downstream":[43],"performance":[44,147],"and":[45,84,93,100,132,156],"sometimes":[47],"lead":[48],"loss":[51],"of":[52,78,98,178,185],"performance,":[53],"known":[54],"as":[55],"negative":[56],"transfer.":[57],"We":[58,103,117],"propose":[59],"RADAR,":[60],"simple,":[62],"geometrically":[63],"grounded":[64],"metric":[65,120],"estimating":[67],"cross-domain":[68,101,133],"transferability":[69,107,151,179],"in":[70,87],"foundation":[71,137],"models.":[72,139],"RADAR":[73,143],"analyzes":[74],"layer-wise":[76],"evolution":[77],"representations":[79],"by":[80,94],"measuring":[81],"angular":[82],"alignments":[83],"relative":[85,148],"changes":[86],"distance":[88],"along":[89],"layer-to-layer":[90],"displacement":[91],"trajectories,":[92],"comparing":[95],"empirical":[96],"distributions":[97],"within-domain":[99],"dynamics.":[102],"hypothesize":[104],"that":[105,175],"related":[109],"divergence":[112],"between":[113],"these":[114],"trajectory":[115],"distributions.":[116],"evaluate":[118],"across":[121],"multiple":[122],"modalities,":[123],"including":[124],"cross-lingual":[125],"sentiment":[126],"classification":[127,135],"text":[129,157],"embedding":[130],"models":[131],"image":[134],"vision":[138,155],"Across":[140],"several":[141,154],"settings,":[142],"provides":[144],"competitive":[145],"predictive":[146],"existing":[150],"metrics":[152],"benchmarks,":[158],"particularly":[160],"strong":[161],"results":[162],"when":[163],"transitions":[165],"are":[166],"smooth":[167],"cleanly":[169],"separated.":[170],"Our":[171],"ablations":[172],"further":[173],"suggest":[174],"effectiveness":[177],"estimation":[180],"depends":[181],"geometry":[184],"model's":[187],"internal":[188],"representation":[189],"space,":[190],"different":[192,195],"modalities":[193],"favoring":[194],"topological":[196],"formulations.":[197]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-26T00:00:00"}
