{"id":"https://openalex.org/W7163178516","doi":"https://doi.org/10.48550/arxiv.2606.00746","title":"Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders","display_name":"Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders","publication_year":2026,"publication_date":"2026-05-30","ids":{"openalex":"https://openalex.org/W7163178516","doi":"https://doi.org/10.48550/arxiv.2606.00746"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.00746","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00746","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":null,"license_id":null,"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.2606.00746","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009071327","display_name":"Yitong Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Yitong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137624909","display_name":"Hongjun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Hongjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137670232","display_name":"Collin McCarthy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"McCarthy, Collin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058387246","display_name":"Hanrong Ye","orcid":"https://orcid.org/0000-0002-7986-6143"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Hanrong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058569454","display_name":"David Wehr","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wehr, David","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137690223","display_name":"Xinhao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xinhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137705567","display_name":"Qi Dou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dou, Qi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137699472","display_name":"Tianfan Xue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Tianfan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084054549","display_name":"Ka Chun Cheung","orcid":"https://orcid.org/0000-0002-2939-4686"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheung, Ka Chun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137687379","display_name":"Simon See","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"See, Simon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025693806","display_name":"Wonmin Byeon","orcid":"https://orcid.org/0000-0002-4780-4749"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Byeon, Wonmin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137623149","display_name":"Ke Chen","orcid":"https://orcid.org/0000-0002-2098-1921"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Ke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137708103","display_name":"Kai Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137662084","display_name":"Jinwei Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Jinwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137665620","display_name":"Hongxu Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Hongxu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137702867","display_name":"Pavlo Molchanov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Molchanov, Pavlo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137668813","display_name":"Jan Kautz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kautz, Jan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137641003","display_name":"Sifei Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Sifei","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/T10036","display_name":"Advanced Neural Network Applications","score":0.3799000084400177,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.3799000084400177,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.11819999665021896,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.04989999905228615,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6011999845504761},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5091999769210815},{"id":"https://openalex.org/keywords/catadioptric-system","display_name":"Catadioptric system","score":0.47049999237060547},{"id":"https://openalex.org/keywords/image-stitching","display_name":"Image stitching","score":0.4537000060081482},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.42809998989105225},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4088999927043915},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.39640000462532043},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.3589000105857849},{"id":"https://openalex.org/keywords/directx","display_name":"DirectX","score":0.32280001044273376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7806000113487244},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6011999845504761},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5091999769210815},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4846999943256378},{"id":"https://openalex.org/C153396827","wikidata":"https://www.wikidata.org/wiki/Q1142960","display_name":"Catadioptric system","level":3,"score":0.47049999237060547},{"id":"https://openalex.org/C29081049","wikidata":"https://www.wikidata.org/wiki/Q1364242","display_name":"Image stitching","level":2,"score":0.4537000060081482},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.42809998989105225},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41670000553131104},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4088999927043915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40630000829696655},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.39640000462532043},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.35350000858306885},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3391999900341034},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3246999979019165},{"id":"https://openalex.org/C544400634","wikidata":"https://www.wikidata.org/wiki/Q188695","display_name":"DirectX","level":2,"score":0.32280001044273376},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.31850001215934753},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.31299999356269836},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.28189998865127563},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2703999876976013},{"id":"https://openalex.org/C2778361833","wikidata":"https://www.wikidata.org/wiki/Q34735","display_name":"Compass","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C70970002","wikidata":"https://www.wikidata.org/wiki/Q189434","display_name":"Multiplexer","level":3,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.00746","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00746","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.00746","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00746","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":null,"license_id":null,"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":{"Vision":[0],"foundation":[1],"models":[2,30],"are":[3],"bottlenecked":[4],"by":[5,203],"the":[6,17,44,61,95,140,171,179,213],"quadratic":[7],"cost":[8,18,180],"of":[9,19,129,181,212],"self-attention,":[10],"which":[11,153],"limits":[12],"usable":[13],"resolution":[14,208],"and":[15,28,42,121,133,159,162,218],"increases":[16],"large-scale":[20],"pretraining.":[21],"Subquadratic":[22],"alternatives":[23],"such":[24],"as":[25,78],"linear":[26],"attention":[27,176],"state-space":[29],"reduce":[31],"this":[32],"cost,":[33],"but":[34,73],"often":[35],"serialize":[36],"images":[37],"into":[38,111,157],"1D":[39],"token":[40],"streams":[41],"weaken":[43],"2D":[45,62,90],"spatial":[46,91],"structure":[47],"important":[48],"for":[49],"vision.":[50],"Generalized":[51],"Spatial":[52],"Propagation":[53],"Networks":[54],"(GSPN)":[55],"instead":[56],"propagate":[57],"context":[58],"directly":[59],"on":[60,89],"grid":[63],"through":[64,98],"line-scan":[65],"recurrences,":[66],"achieving":[67],"near-linear":[68],"complexity":[69],"without":[70,178],"positional":[71],"embeddings,":[72],"have":[74],"seen":[75],"little":[76],"use":[77],"foundation-scale":[79,85,183],"encoders.":[80],"We":[81],"present":[82],"C-GSPN,":[83],"a":[84,102,112,122,145,164,210,220],"vision":[86],"encoder":[87],"based":[88],"propagation.":[92],"C-GSPN":[93,190],"makes":[94],"operator":[96],"practical":[97],"three":[99],"improvements:":[100],"(1)":[101],"fast":[103],"GSPN":[104,142],"CUDA":[105],"kernel":[106],"that":[107,169],"fuses":[108],"per-step":[109],"launches":[110],"single":[113],"warp-specialized":[114],"implementation":[115],"with":[116,150,186,196,209,227],"shared-memory":[117],"tiling,":[118],"coalesced":[119],"access,":[120],"compact":[123],"multi-channel":[124],"propagation,":[125],"reaching":[126],"over":[127],"90%":[128],"peak":[130],"memory":[131],"bandwidth":[132],"running":[134],"up":[135],"to":[136,206],"40--52x":[137],"faster":[138],"than":[139],"original":[141],"implementation;":[143],"(2)":[144],"compressed":[146],"latent-space":[147],"propagation":[148],"block":[149,223],"fused":[151],"normalization,":[152],"turns":[154],"kernel-level":[155],"speed":[156],"block-":[158],"model-level":[160],"efficiency;":[161],"(3)":[163],"two-stage":[165],"cross-operator":[166],"distillation":[167],"recipe":[168],"trains":[170],"new":[172],"architecture":[173],"from":[174,216],"an":[175,192],"teacher":[177],"from-scratch":[182],"training.":[184],"Distilled":[185],"600M":[187],"image-text":[188],"pairs,":[189],"matches":[191],"isomorphic":[193],"ViT":[194],"baseline":[195],"15%":[197],"fewer":[198],"parameters,":[199],"improves":[200],"ADE20K":[201],"segmentation":[202],"+2.1%,":[204],"transfers":[205],"high":[207],"fraction":[211],"data":[214],"needed":[215],"scratch,":[217],"delivers":[219],"4x":[221],"end-to-end":[222],"speedup":[224],"at":[225],"2K":[226],"single-pass,":[228],"tiling-free":[229],"inference.":[230]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-03T00:00:00"}
