{"id":"https://openalex.org/W7160328903","doi":"https://doi.org/10.48550/arxiv.2605.01711","title":"Linear-Time Global Visual Modeling without Explicit Attention","display_name":"Linear-Time Global Visual Modeling without Explicit Attention","publication_year":2026,"publication_date":"2026-05-03","ids":{"openalex":"https://openalex.org/W7160328903","doi":"https://doi.org/10.48550/arxiv.2605.01711"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.01711","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01711","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.2605.01711","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135404085","display_name":"Ruize He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Ruize","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102210006","display_name":"Dongchen Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Dongchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135378919","display_name":"Gao Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Gao","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.19660000503063202,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.19660000503063202,"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":0.13850000500679016,"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/T10799","display_name":"Data Visualization and Analytics","score":0.07599999755620956,"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/computation","display_name":"Computation","score":0.5705999732017517},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5526999831199646},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.54830002784729},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5185999870300293},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.5073000192642212},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.3621000051498413},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3513000011444092}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.729200005531311},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5705999732017517},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5526999831199646},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.54830002784729},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5185999870300293},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.5073000192642212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45730000734329224},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3853999972343445},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3621000051498413},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3513000011444092},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3361999988555908},{"id":"https://openalex.org/C73301696","wikidata":"https://www.wikidata.org/wiki/Q5469984","display_name":"Formalism (music)","level":3,"score":0.3133000135421753},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2980000078678131},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.2718999981880188},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.01711","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01711","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.2605.01711","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01711","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Existing":[0],"research":[1],"largely":[2],"attributes":[3],"the":[4,12,81],"global":[5,58,82,98],"sequence":[6,97,156],"modeling":[7,59,99],"capability":[8],"of":[9,15,80],"Transformers":[10],"to":[11,148],"explicit":[13,63,110,149],"computation":[14],"attention":[16,37],"weights,":[17],"a":[18,31,43,77,90,143],"process":[19,70],"that":[20,36,136],"inherently":[21],"incurs":[22],"quadratic":[23],"computational":[24],"complexity.":[25],"In":[26],"this":[27,53,86],"work,":[28],"we":[29,34,55,88,94,115],"offer":[30],"novel":[32],"perspective:":[33],"demonstrate":[35,135],"can":[38,93,139],"be":[39],"mathematically":[40],"reframed":[41],"as":[42,62,67,76,142],"Multi-Layer":[44],"Perceptron":[45],"(MLP)":[46],"equipped":[47],"with":[48],"dynamically":[49,72],"predicted":[50],"parameters.":[51],"Through":[52],"lens,":[54],"explain":[56],"attention's":[57],"power":[60],"not":[61],"token-wise":[64],"aggregation,":[65],"but":[66],"an":[68],"implicit":[69],"where":[71],"generated":[73],"parameters":[74],"act":[75],"compressed":[78],"representation":[79],"context.":[83],"Inspired":[84],"by":[85],"insight,":[87],"investigate":[89],"fundamental":[91],"question:":[92],"achieve":[95],"Transformer-level":[96],"entirely":[100],"through":[101],"dynamic":[102,118,137],"parameterization":[103,138],"while":[104],"maintaining":[105],"linear":[106],"complexity,":[107],"effectively":[108],"replacing":[109],"attention?":[111],"To":[112],"explore":[113],"this,":[114],"design":[116],"various":[117],"parameter":[119],"prediction":[120],"strategies":[121],"and":[122],"integrate":[123],"them":[124],"into":[125],"standard":[126],"network":[127],"layers.":[128],"Extensive":[129],"empirical":[130],"studies":[131],"on":[132],"vision":[133],"models":[134],"indeed":[140],"serve":[141],"highly":[144],"effective,":[145],"linear-complexity":[146],"alternative":[147],"attention,":[150],"opening":[151],"new":[152],"pathways":[153],"for":[154],"efficient":[155],"modeling.":[157],"Code":[158],"is":[159],"available":[160],"at":[161],"https://github.com/LeapLabTHU/WeightFormer.":[162]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-06T00:00:00"}