乐胖代购免代理版

{"id":"https://openalex.org/W4303648967","doi":"https://doi.org/10.48550/arxiv.2210.03117","title":"MaPLe: Multi-modal Prompt Learning","display_name":"MaPLe: Multi-modal Prompt Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4303648967","doi":"https://doi.org/10.48550/arxiv.2210.03117"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2210.03117","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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2210.03117","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077014645","display_name":"Muhammad Uzair Khattak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khattak, Muhammad Uzair","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064948724","display_name":"Hanoona Rasheed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rasheed, Hanoona","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034370385","display_name":"Muhammad Maaz","orcid":"https://orcid.org/0000-0002-3869-631X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maaz, Muhammad","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101483978","display_name":"Salman Khan","orcid":"https://orcid.org/0000-0001-8732-3395"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Salman","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100760570","display_name":"Fahad Shahbaz Khan","orcid":"https://orcid.org/0000-0002-4263-3143"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Fahad Shahbaz","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"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":3,"citation_normalized_percentile":{"value":0.854089,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":76,"max":80},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9995,"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":0.9995,"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":0.9942,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9664,"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/representation","display_name":"Representation","score":0.4706544},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4390835}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7989599},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6901087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.56722224},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5620512},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5357918},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5040116},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4706544},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.46566796},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4390835},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43601692},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.43386948},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37860918},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.10980436},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.08805859},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2210.03117","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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2210.03117","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2210.03117","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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality education","score":0.78}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W43109613","https://openalex.org/W3162204513","https://openalex.org/W3083152911","https://openalex.org/W2997567050","https://openalex.org/W2371138613","https://openalex.org/W2359952343","https://openalex.org/W2239445980","https://openalex.org/W2080152487","https://openalex.org/W2075445622","https://openalex.org/W2048963458"],"abstract_inverted_index":{"Pre-trained":[0],"vision-language":[1,127],"(V-L)":[2],"models":[3,219],"such":[4],"as":[5,50],"CLIP":[6,45,56,73],"have":[7],"shown":[8],"excellent":[9],"generalization":[10,172],"ability":[11],"to":[12,19,33,54,65,86,111,129,148,155,173],"downstream":[13,58,94],"tasks.":[14,59],"However,":[15],"they":[16],"are":[17,220],"sensitive":[18],"the":[20,38,51,84,115,126,151,162,185],"choice":[21],"of":[22,30,72,164,171,198],"input":[23],"text":[24],"prompts":[25,49,128,143],"and":[26,108,117,133,179,193,203,217],"require":[27],"careful":[28],"selection":[29],"prompt":[31],"templates":[32],"perform":[34],"well.":[35],"Inspired":[36],"by":[37],"Natural":[39],"Language":[40],"Processing":[41],"(NLP)":[42],"literature,":[43],"recent":[44],"adaptation":[46],"approaches":[47],"learn":[48,141],"textual":[52],"inputs":[53],"fine-tune":[55],"for":[57,105],"We":[60,160],"note":[61],"that":[62],"using":[63],"prompting":[64],"adapt":[66],"representations":[67],"in":[68],"a":[69,93],"single":[70],"branch":[71],"(language":[74],"or":[75],"vision)":[76],"is":[77],"sub-optimal":[78],"since":[79],"it":[80],"does":[81],"not":[82],"allow":[83,156],"flexibility":[85],"dynamically":[87],"adjust":[88],"both":[89,106],"representation":[90],"spaces":[91],"on":[92,167,200,205],"task.":[95],"In":[96],"this":[97],"work,":[98],"we":[99,140],"propose":[100],"Multi-modal":[101],"Prompt":[102],"Learning":[103],"(MaPLe)":[104],"vision":[107,116],"language":[109,118],"branches":[110],"improve":[112],"alignment":[113],"between":[114,125],"representations.":[119],"Our":[120,215],"design":[121],"promotes":[122],"strong":[123],"coupling":[124],"ensure":[130],"mutual":[131],"synergy":[132],"discourages":[134],"learning":[135],"independent":[136],"uni-modal":[137],"solutions.":[138],"Further,":[139],"separate":[142],"across":[144],"different":[145],"early":[146],"stages":[147],"progressively":[149],"model":[150],"stage-wise":[152],"feature":[153],"relationships":[154],"rich":[157],"context":[158],"learning.":[159],"evaluate":[161],"effectiveness":[163],"our":[165],"approach":[166],"three":[168],"representative":[169],"tasks":[170],"novel":[174,201],"classes,":[175],"new":[176],"target":[177],"datasets":[178],"unseen":[180],"domain":[181],"shifts.":[182],"Compared":[183],"with":[184],"state-of-the-art":[186],"method":[187],"Co-CoOp,":[188],"MaPLe":[189],"exhibits":[190],"favorable":[191],"performance":[192],"achieves":[194],"an":[195],"absolute":[196],"gain":[197],"3.45%":[199],"classes":[202],"2.72%":[204],"overall":[206],"harmonic-mean,":[207],"averaged":[208],"over":[209],"11":[210],"diverse":[211],"image":[212],"recognition":[213],"datasets.":[214],"code":[216],"pre-trained":[218],"available":[221],"at":[222],"https://github.com/muzairkhattak/multimodal-prompt-learning.":[223]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4303648967","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-01-04T18:54:13.586707","created_date":"2022-10-08"}