{"id":"https://openalex.org/W4417339469","doi":"https://doi.org/10.1109/ictai66417.2025.00110","title":"SCALAR: Self-Calibrating Adaptive Latent Attention Representation Learning","display_name":"SCALAR: Self-Calibrating Adaptive Latent Attention Representation Learning","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W4417339469","doi":"https://doi.org/10.1109/ictai66417.2025.00110"},"language":null,"primary_location":{"id":"doi:10.1109/ictai66417.2025.00110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictai66417.2025.00110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI)","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/A5113150812","display_name":"Farwa Abbas","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Farwa Abbas","raw_affiliation_strings":["Imperial College London,UK"],"affiliations":[{"raw_affiliation_string":"Imperial College London,UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101660408","display_name":"Hussain Ahmad","orcid":"https://orcid.org/0000-0001-8815-7587"},"institutions":[{"id":"https://openalex.org/I5681781","display_name":"University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hussain Ahmad","raw_affiliation_strings":["The University of Adelaide,Australia"],"affiliations":[{"raw_affiliation_string":"The University of Adelaide,Australia","institution_ids":["https://openalex.org/I5681781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016821538","display_name":"Claudia Szabo","orcid":"https://orcid.org/0000-0003-2501-1155"},"institutions":[{"id":"https://openalex.org/I5681781","display_name":"University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Claudia Szabo","raw_affiliation_strings":["The University of Adelaide,Australia"],"affiliations":[{"raw_affiliation_string":"The University of Adelaide,Australia","institution_ids":["https://openalex.org/I5681781"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113150812"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21041861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"762","last_page":"769"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.20810000598430634,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.20810000598430634,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.1808999925851822,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.16329999268054962,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.7357000112533569},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6740000247955322},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5652999877929688},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5306000113487244},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.462799996137619},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.436599999666214},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42089998722076416},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.3197000026702881},{"id":"https://openalex.org/keywords/feature-model","display_name":"Feature model","score":0.3192000091075897}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7839000225067139},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.7357000112533569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7006000280380249},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6740000247955322},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5652999877929688},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5475000143051147},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5306000113487244},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.462799996137619},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.436599999666214},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42089998722076416},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.3192000091075897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3025999963283539},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictai66417.2025.00110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictai66417.2025.00110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320978","display_name":"University of Adelaide","ror":"https://ror.org/00892tw58"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1992259099","https://openalex.org/W2086286404","https://openalex.org/W2095211414","https://openalex.org/W2163922914","https://openalex.org/W2752782242","https://openalex.org/W2785947426","https://openalex.org/W2898085636","https://openalex.org/W2899788782","https://openalex.org/W3034421924","https://openalex.org/W3096561213","https://openalex.org/W3127452014","https://openalex.org/W3138498491","https://openalex.org/W3163510368","https://openalex.org/W3174086521","https://openalex.org/W3210246971","https://openalex.org/W4206095984","https://openalex.org/W4206564180","https://openalex.org/W4220952101","https://openalex.org/W4221051301","https://openalex.org/W4292289226","https://openalex.org/W4380681094","https://openalex.org/W4391444806","https://openalex.org/W4392500218","https://openalex.org/W4400902169","https://openalex.org/W4404646531","https://openalex.org/W4406895127"],"related_works":[],"abstract_inverted_index":{"High-dimensional,":[0],"heterogeneous":[1],"data":[2],"with":[3,36],"complex":[4,29],"feature":[5,61,101],"interactions":[6,47],"pose":[7],"significant":[8],"challenges":[9],"for":[10],"traditional":[11],"predictive":[12,84],"modeling":[13],"approaches.":[14],"While":[15],"Projection":[16],"to":[17,27,55,65,124],"Latent":[18],"Structures":[19],"(PLS)":[20],"remains":[21],"a":[22,79],"popular":[23],"technique,":[24],"it":[25,69],"struggles":[26],"model":[28],"non-linear":[30],"relationships,":[31],"especially":[32],"in":[33,120],"multivariate":[34],"systems":[35],"high-dimensional":[37],"correlation":[38],"structures.":[39],"This":[40],"challenge":[41],"is":[42],"further":[43],"compounded":[44],"by":[45],"simultaneous":[46],"across":[48,128],"multiple":[49],"scales,":[50],"where":[51],"local":[52,109],"processing":[53],"fails":[54],"capture":[56,107],"crossgroup":[57],"dependencies.":[58],"Additionally,":[59],"static":[60],"weighting":[62],"limits":[63],"adaptability":[64],"contextual":[66],"variations,":[67],"as":[68],"ignores":[70],"sample-specific":[71],"relevance.":[72],"To":[73],"address":[74],"these":[75],"limitations,":[76],"we":[77],"propose":[78],"novel":[80,87],"method":[81],"that":[82,98],"enhances":[83],"performance":[85,121],"through":[86],"architectural":[88],"innovations.":[89],"Our":[90],"architecture":[91],"introduces":[92],"an":[93],"adaptive":[94],"kernel-based":[95],"attention":[96],"mechanism":[97],"processes":[99],"distinct":[100],"groups":[102],"separately":[103],"before":[104],"integration,":[105],"enabling":[106],"of":[108],"patterns":[110],"while":[111],"preserving":[112],"global":[113],"relationships.":[114],"Experimental":[115],"results":[116],"show":[117],"substantial":[118],"improvements":[119],"metrics,":[122],"compared":[123],"the":[125],"state-of-the-art":[126],"methods":[127],"diverse":[129],"datasets.":[130]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-12-15T00:00:00"}
