{"id":"https://openalex.org/W4380361718","doi":"https://doi.org/10.48550/arxiv.2306.05963","title":"Adaptive Contextual Perception: How to Generalize to New Backgrounds and Ambiguous Objects","display_name":"Adaptive Contextual Perception: How to Generalize to New Backgrounds and Ambiguous Objects","publication_year":2023,"publication_date":"2023-06-09","ids":{"openalex":"https://openalex.org/W4380361718","doi":"https://doi.org/10.48550/arxiv.2306.05963"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2306.05963","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.05963","pdf_url":"https://arxiv.org/pdf/2306.05963","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2306.05963","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033138733","display_name":"Zhuofan Ying","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ying, Zhuofan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013096489","display_name":"Peter Hase","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hase, Peter","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5001987532","display_name":"Mohit Bansal","orcid":"https://orcid.org/0000-0001-5522-1351"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bansal, Mohit","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":true,"cited_by_count":1,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.988099992275238,"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"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.988099992275238,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9858999848365784,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9616000056266785,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6993967890739441},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6646742224693298},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6434675455093384},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5648208260536194},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5442940592765808},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5270757079124451},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4961636960506439},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.42480599880218506},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42399176955223083},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42156508564949036},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.41932815313339233},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14441847801208496}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6993967890739441},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6646742224693298},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6434675455093384},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5648208260536194},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5442940592765808},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5270757079124451},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4961636960506439},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.42480599880218506},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42399176955223083},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42156508564949036},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.41932815313339233},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14441847801208496},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2306.05963","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.05963","pdf_url":"https://arxiv.org/pdf/2306.05963","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2306.05963","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2306.05963","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"pmh:oai:arXiv.org:2306.05963","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.05963","pdf_url":"https://arxiv.org/pdf/2306.05963","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G2921176242","display_name":null,"funder_award_id":"W911NF2110220","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G5599941371","display_name":null,"funder_award_id":"N00014-23-1-2356","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G7357862116","display_name":null,"funder_award_id":"N66001-19-2-4031","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G8215844777","display_name":null,"funder_award_id":"N66001-19","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4380361718.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W2180954594","https://openalex.org/W3211292372"],"abstract_inverted_index":{"Biological":[0],"vision":[1,33,247],"systems":[2],"make":[3],"adaptive":[4],"use":[5,36,155],"of":[6,124,168,243,261],"context":[7,37],"to":[8,47,99,144,151,164,206,219,238],"recognize":[9],"objects":[10,23],"in":[11,24,75,83,95,101,117,186,230],"new":[12,216],"settings":[13,58,88],"with":[14,175],"novel":[15],"contexts":[16,61],"as":[17,19,130],"well":[18],"occluded":[20],"or":[21,66],"blurry":[22],"familiar":[25],"settings.":[26],"In":[27,236],"this":[28,131],"paper,":[29],"we":[30,53,154,171,214],"investigate":[31],"how":[32],"models":[34,92,248],"adaptively":[35],"for":[38,135],"out-of-distribution":[39],"(OOD)":[40],"generalization":[41,241],"and":[42,89,139,159,170,179,189,203,233,256],"leverage":[43],"our":[44,160],"analysis":[45,158],"results":[46],"improve":[48,111],"model":[49,81,148,221],"OOD":[50,57,87,128,152,234],"generalization.":[51,222],"First,":[52],"formulate":[54],"two":[55,85],"distinct":[56],"where":[59],"the":[60,70,102,118,122,147,240],"are":[62,183],"either":[63],"irrelevant":[64],"(Background-Invariance)":[65],"beneficial":[67],"(Object-Disambiguation),":[68],"reflecting":[69],"diverse":[71],"contextual":[72],"challenges":[73],"faced":[74],"biological":[76,244],"vision.":[77],"We":[78,192],"then":[79],"analyze":[80],"performance":[82],"these":[84,195],"different":[86],"demonstrate":[90,207],"that":[91,93,173],"excel":[94],"one":[96,113],"setting":[97,114],"tend":[98],"struggle":[100],"other.":[103,119],"Notably,":[104],"prior":[105],"works":[106],"on":[107,112,200,211],"learning":[108],"causal":[109,198,209],"features":[110],"but":[115],"hurt":[116],"This":[120],"underscores":[121],"importance":[123],"generalizing":[125],"across":[126],"both":[127,136,231,259],"settings,":[129],"ability":[132],"is":[133],"crucial":[134],"human":[137],"cognition":[138],"robust":[140],"AI":[141],"systems.":[142],"Next,":[143],"better":[145],"understand":[146],"properties":[149],"contributing":[150],"generalization,":[153],"representational":[156],"geometry":[157],"own":[161],"probing":[162],"methods":[163,218,224],"examine":[165],"a":[166],"population":[167],"models,":[169],"discover":[172],"those":[174],"more":[176,184],"factorized":[177,251],"representations":[178,255],"appropriate":[180],"feature":[181,204],"weighting":[182,205],"successful":[185],"handling":[187],"Background-Invariance":[188],"Object-Disambiguation":[190],"tests.":[191,235],"further":[193],"validate":[194],"findings":[196],"through":[197],"intervention":[199],"representation":[201],"factorization":[202],"their":[208],"effect":[210],"performance.":[212],"Lastly,":[213],"propose":[215],"augmentation":[217],"enhance":[220],"These":[223],"outperform":[225],"strong":[226],"baselines,":[227],"yielding":[228],"improvements":[229],"in-distribution":[232],"conclusion,":[237],"replicate":[239],"abilities":[242],"vision,":[245],"computer":[246],"must":[249],"have":[250],"object":[252],"vs.":[253],"background":[254],"appropriately":[257],"weight":[258],"kinds":[260],"features.":[262]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2023-06-13T00:00:00"}