{"id":"https://openalex.org/W7163523875","doi":"https://doi.org/10.48550/arxiv.2606.04433","title":"Stateful Visual Encoders for Vision-Language Models","display_name":"Stateful Visual Encoders for Vision-Language Models","publication_year":2026,"publication_date":"2026-06-03","ids":{"openalex":"https://openalex.org/W7163523875","doi":"https://doi.org/10.48550/arxiv.2606.04433"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.04433","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04433","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.2606.04433","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137842285","display_name":"Zirui Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zirui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064951946","display_name":"Junwei Yu","orcid":"https://orcid.org/0000-0003-2737-9789"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Junwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084801169","display_name":"Adam Yala","orcid":"https://orcid.org/0000-0001-9576-2590"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yala, Adam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137871851","display_name":"David M. Chan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chan, David M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137873331","display_name":"Joseph E. Gonzalez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gonzalez, Joseph E.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137877390","display_name":"Trevor Darrell","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Darrell, Trevor","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9327999949455261,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9327999949455261,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.016899999231100082,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.007699999958276749,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/stateful-firewall","display_name":"Stateful firewall","score":0.9261999726295471},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6646999716758728},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5299999713897705},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4620000123977661},{"id":"https://openalex.org/keywords/visual-memory","display_name":"Visual memory","score":0.4004000127315521},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.39739999175071716},{"id":"https://openalex.org/keywords/visual-reasoning","display_name":"Visual reasoning","score":0.37279999256134033}],"concepts":[{"id":"https://openalex.org/C22927095","wikidata":"https://www.wikidata.org/wiki/Q1784206","display_name":"Stateful firewall","level":3,"score":0.9261999726295471},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7633000016212463},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6646999716758728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5738000273704529},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5299999713897705},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4620000123977661},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.414900004863739},{"id":"https://openalex.org/C178278151","wikidata":"https://www.wikidata.org/wiki/Q7936607","display_name":"Visual memory","level":3,"score":0.4004000127315521},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.37279999256134033},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31690001487731934},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.30880001187324524},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2937000095844269},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C2780878386","wikidata":"https://www.wikidata.org/wiki/Q1659648","display_name":"Visual language","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.25600001215934753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.04433","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04433","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.2606.04433","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04433","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":[{"score":0.49922966957092285,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Vision-language":[0],"models":[1,167],"(VLMs)":[2],"are":[3,125],"increasingly":[4],"used":[5],"in":[6,18,168],"multi-image,":[7],"multi-turn":[8],"agentic":[9],"settings":[10],"where":[11,153],"decisions":[12],"depend":[13],"on":[14,93,108,141],"visual":[15,22,32,47,91,95,116,119],"changes.":[16],"However,":[17],"existing":[19],"open-weight":[20],"VLMs,":[21],"comparisons":[23],"happen":[24],"only":[25],"inside":[26],"the":[27,31,45,60,76,80],"language":[28,61,130],"model,":[29],"while":[30],"encoder":[33],"itself":[34],"remains":[35],"stateless:":[36],"each":[37,90],"image":[38,148],"is":[39],"encoded":[40],"independently,":[41],"without":[42],"access":[43],"to":[44,66],"prior":[46,94],"context.":[48],"As":[49],"a":[50,64,84],"result,":[51],"small":[52],"but":[53],"task-critical":[54],"changes":[55,72],"may":[56],"be":[57],"attenuated":[58],"before":[59],"model":[62,131,140],"has":[63],"chance":[65],"compare":[67],"them,":[68],"especially":[69],"when":[70],"those":[71],"do":[73],"not":[74],"affect":[75],"high-level":[77],"semantics":[78],"of":[79],"scene.":[81],"We":[82],"introduce":[83],"Stateful":[85],"Visual":[86],"Encoder,":[87],"which":[88],"conditions":[89],"representation":[92],"features.":[96],"Under":[97],"supervised":[98],"finetuning,":[99],"VLMs":[100],"equipped":[101],"with":[102],"stateful":[103,154],"encoders":[104,155],"achieve":[105],"consistent":[106,126],"improvements":[107,124],"controlled":[109],"tasks":[110],"involving":[111],"cross-image":[112],"spatial":[113],"aggregation,":[114],"multi-object":[115],"differencing,":[117],"and":[118,133,150,161],"trajectory":[120],"behavior":[121],"cloning.":[122],"These":[123],"across":[127],"input":[128],"resolutions,":[129],"sizes,":[132],"VLM":[134,159],"backbones.":[135],"Finally,":[136],"we":[137],"validate":[138],"our":[139],"real-world":[142],"tasks,":[143],"including":[144],"longitudinal":[145],"radiology,":[146],"fine-grained":[147],"comparison,":[149],"remote":[151],"sensing,":[152],"consistently":[156],"improve":[157],"generalist":[158],"baselines":[160],"can":[162],"match":[163],"or":[164],"surpass":[165],"specialized":[166],"selected":[169],"domains.":[170],"Project":[171],"page:":[172],"https://statefulvisualencoders.github.io/":[173]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-05T00:00:00"}