{"id":"https://openalex.org/W7152613386","doi":"https://doi.org/10.48550/arxiv.2604.06748","title":"From Static to Interactive: Adapting Visual in-Context Learners for User-Driven Tasks","display_name":"From Static to Interactive: Adapting Visual in-Context Learners for User-Driven Tasks","publication_year":2026,"publication_date":"2026-04-08","ids":{"openalex":"https://openalex.org/W7152613386","doi":"https://doi.org/10.48550/arxiv.2604.06748"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.06748","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06748","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.06748","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133275000","display_name":"Carlos Schmidt","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schmidt, Carlos","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5091379199","display_name":"Simon Rei\u00df","orcid":"https://orcid.org/0000-0003-1953-6211"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rei\u00df, Simon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"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":0.35010001063346863,"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":0.35010001063346863,"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":0.15950000286102295,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.1371999979019165,"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/leverage","display_name":"Leverage (statistics)","score":0.6435999870300293},{"id":"https://openalex.org/keywords/interactivity","display_name":"Interactivity","score":0.5644000172615051},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5271999835968018},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.44749999046325684},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41519999504089355},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.39959999918937683},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.3806999921798706},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.3695000112056732},{"id":"https://openalex.org/keywords/icub","display_name":"iCub","score":0.36039999127388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8219000101089478},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6435999870300293},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.6279000043869019},{"id":"https://openalex.org/C144430266","wikidata":"https://www.wikidata.org/wiki/Q839721","display_name":"Interactivity","level":2,"score":0.5644000172615051},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5271999835968018},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5235999822616577},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41519999504089355},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.39959999918937683},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3806999921798706},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.3695000112056732},{"id":"https://openalex.org/C111151474","wikidata":"https://www.wikidata.org/wiki/Q1653368","display_name":"iCub","level":4,"score":0.36039999127388},{"id":"https://openalex.org/C2779321571","wikidata":"https://www.wikidata.org/wiki/Q7936605","display_name":"Visual learning","level":2,"score":0.33980000019073486},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.33730000257492065},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.3264000117778778},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C2776716048","wikidata":"https://www.wikidata.org/wiki/Q6045290","display_name":"Interactive Learning","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C135641252","wikidata":"https://www.wikidata.org/wiki/Q738567","display_name":"Multimodal interaction","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C2777055276","wikidata":"https://www.wikidata.org/wiki/Q7936580","display_name":"Visual approach","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.26660001277923584},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.2549000084400177},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.06748","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06748","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.06748","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06748","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":"article"},"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":{"Visual":[0],"in-context":[1,122,166,196,257],"learning":[2,167,197],"models":[3,27,173,198],"are":[4],"designed":[5],"to":[6,8,38,45,57,75,105,118,171,182,200],"adapt":[7,37],"new":[9,39],"tasks":[10],"by":[11,81,151],"leveraging":[12],"a":[13,30,89,98,102,115],"set":[14],"of":[15,164,221],"example":[16,157],"input-output":[17,158],"pairs,":[18,159],"enabling":[19,136,169],"rapid":[20],"generalization":[21],"without":[22,177],"task-specific":[23],"fine-tuning.":[24],"However,":[25],"these":[26],"operate":[28],"in":[29,69,101,215],"fundamentally":[31],"static":[32,120,248],"paradigm:":[33],"while":[34],"they":[35,41],"can":[36],"tasks,":[40],"lack":[42],"any":[43],"mechanism":[44],"incorporate":[46],"user-provided":[47],"guidance":[48,208],"signals":[49],"such":[50,143],"as":[51,144],"scribbles,":[52,145],"clicks,":[53,146],"or":[54,59,96,147],"bounding":[55],"boxes":[56],"steer":[58,184],"refine":[60],"the":[61,83,125,156,162,244],"prediction":[62],"process.":[63],"This":[64],"limitation":[65],"is":[66],"particularly":[67,124],"restrictive":[68],"real-world":[70],"applications,":[71],"where":[72],"users":[73,170],"want":[74],"actively":[76],"guide":[77],"model":[78,185],"predictions,":[79],"e.g.,":[80],"highlighting":[82],"target":[84],"object":[85,237],"for":[86,224,229,235,254],"segmentation,":[87,226],"indicating":[88],"region":[90],"which":[91],"should":[92],"be":[93],"visually":[94],"altered,":[95],"isolating":[97],"specific":[99],"person":[100],"complex":[103],"scene":[104],"run":[106],"targeted":[107],"pose":[108],"estimation.":[109],"In":[110,210],"this":[111],"work,":[112],"we":[113,160],"propose":[114],"simple":[116],"method":[117,213],"transform":[119],"visual":[121,141,165,195,256],"learners,":[123],"DeLVM":[126],"approach,":[127],"into":[128,155],"highly":[129],"controllable,":[130,216],"user-driven":[131],"systems,":[132],"i.e.,":[133],"Interactive":[134],"DeLVM,":[135],"seamless":[137],"interaction":[138,203],"through":[139],"natural":[140],"cues":[142],"drawing":[148],"boxes.":[149],"Specifically,":[150],"encoding":[152],"interactions":[153,176],"directly":[154],"keep":[161],"philosophy":[163],"intact:":[168],"prompt":[172],"with":[174,187],"unseen":[175],"fine-tuning":[178],"and":[179,232,251],"empowering":[180],"them":[181],"dynamically":[183],"predictions":[186],"personalized":[188],"interactions.":[189],"Our":[190],"experiments":[191],"demonstrate":[192],"that":[193],"SOTA":[194],"fail":[199],"effectively":[201],"leverage":[202],"cues,":[204],"often":[205],"ignoring":[206],"user":[207],"entirely.":[209],"contrast,":[211],"our":[212,241],"excels":[214],"user-guided":[217],"scenarios,":[218],"achieving":[219],"improvements":[220],"$+7.95%$":[222],"IoU":[223],"interactive":[225,236],"$+2.46$":[227],"PSNR":[228],"directed":[230],"super-resolution,":[231],"$-3.14%$":[233],"LPIPS":[234],"removal.":[238],"With":[239],"this,":[240],"work":[242],"bridges":[243],"gap":[245],"between":[246],"rigid":[247],"task":[249],"adaptation":[250],"fluid":[252],"interactivity":[253],"user-centric":[255],"learning.":[258]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-10T00:00:00"}