{"id":"https://openalex.org/W7128026853","doi":"https://doi.org/10.48550/arxiv.2602.05598","title":"CAViT -- Channel-Aware Vision Transformer for Dynamic Feature Fusion","display_name":"CAViT -- Channel-Aware Vision Transformer for Dynamic Feature Fusion","publication_year":2026,"publication_date":"2026-02-05","ids":{"openalex":"https://openalex.org/W7128026853","doi":"https://doi.org/10.48550/arxiv.2602.05598"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.05598","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033803468","display_name":"Aon Safdar","orcid":"https://orcid.org/0000-0003-3039-1017"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Safdar, Aon","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102745668","display_name":"Mohamed Saadeldin","orcid":"https://orcid.org/0000-0003-4104-9524"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saadeldin, Mohamed","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033803468"],"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/T11094","display_name":"Face Recognition and Perception","score":0.2287999987602234,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.2287999987602234,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.13570000231266022,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.12600000202655792,"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/security-token","display_name":"Security token","score":0.4984000027179718},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.4948999881744385},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4503999948501587},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43720000982284546},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4350999891757965},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4350000023841858},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4131999909877777},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3407000005245209}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7267000079154968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6068999767303467},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.4984000027179718},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.4948999881744385},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4503999948501587},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43720000982284546},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4350999891757965},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4350000023841858},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4212999939918518},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4131999909877777},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.33500000834465027},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.3255999982357025},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.29809999465942383},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.25200000405311584}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.05598","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.05598","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.05598","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":"pmh:doi:10.48550/arxiv.2602.05598","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"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":{"Vision":[0],"Transformers":[1],"(ViTs)":[2],"have":[3],"demonstrated":[4],"strong":[5],"performance":[6],"across":[7,102],"a":[8,43,52],"range":[9],"of":[10,147],"computer":[11],"vision":[12],"tasks":[13],"by":[14,68,119,131],"modeling":[15],"long-range":[16],"spatial":[17,65],"interactions":[18],"via":[19],"self-attention.":[20],"However,":[21],"channel-wise":[22,69],"mixing":[23,89],"in":[24,62,123],"ViTs":[25],"remains":[26],"static,":[27],"relying":[28],"on":[29,80],"fixed":[30],"multilayer":[31],"perceptrons":[32],"(MLPs)":[33],"that":[34,46],"lack":[35],"adaptability":[36],"to":[37,74,121],"input":[38],"content.":[39],"We":[40,99],"introduce":[41],"'CAViT',":[42],"dual-attention":[44],"architecture":[45],"replaces":[47],"the":[48,72,115,145],"static":[49],"MLP":[50],"with":[51],"dynamic,":[53],"attention-based":[54],"mechanism":[55],"for":[56],"feature":[57,77],"interaction.":[58],"Each":[59],"Transformer":[60],"block":[61],"CAViT":[63,101],"performs":[64],"self-attention":[66],"followed":[67],"self-attention,":[70],"allowing":[71],"model":[73],"dynamically":[75],"recalibrate":[76],"representations":[78],"based":[79],"global":[81],"image":[82],"context.":[83],"This":[84],"unified":[85],"and":[86,109,129,139],"content-aware":[87],"token":[88,150],"strategy":[90],"enhances":[91],"representational":[92],"expressiveness":[93],"without":[94],"increasing":[95],"depth":[96],"or":[97],"complexity.":[98],"validate":[100],"five":[103],"benchmark":[104],"datasets":[105],"spanning":[106],"both":[107],"natural":[108],"medical":[110],"domains,":[111],"where":[112],"it":[113],"outperforms":[114],"standard":[116],"ViT":[117],"baseline":[118],"up":[120],"+3.6%":[122],"accuracy,":[124],"while":[125],"reducing":[126],"parameter":[127],"count":[128],"FLOPs":[130],"over":[132],"30%.":[133],"Qualitative":[134],"attention":[135],"maps":[136],"reveal":[137],"sharper":[138],"semantically":[140],"meaningful":[141],"activation":[142],"patterns,":[143],"validating":[144],"effectiveness":[146],"our":[148],"attention-driven":[149],"mixing.":[151]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-07T00:00:00"}