{"id":"https://openalex.org/W7131646560","doi":"https://doi.org/10.48550/arxiv.2602.21854","title":"FewMMBench: A Benchmark for Multimodal Few-Shot Learning","display_name":"FewMMBench: A Benchmark for Multimodal Few-Shot Learning","publication_year":2026,"publication_date":"2026-02-25","ids":{"openalex":"https://openalex.org/W7131646560","doi":"https://doi.org/10.48550/arxiv.2602.21854"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.21854","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126877054","display_name":"Mustafa Dogan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Dogan, Mustafa","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039806824","display_name":"\u0130lker Kesen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kesen, Ilker","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126946074","display_name":"Iacer Calixto","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Calixto, Iacer","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004736226","display_name":"Aykut Erdem","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Erdem, Aykut","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5053961182","display_name":"Erkut Erdem","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Erdem, Erkut","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5126877054"],"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.5758000016212463,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.5758000016212463,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.24570000171661377,"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/T10028","display_name":"Topic Modeling","score":0.07159999758005142,"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/suite","display_name":"Suite","score":0.7820000052452087},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7639999985694885},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5975000262260437},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5913000106811523},{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.5866000056266785},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5401999950408936},{"id":"https://openalex.org/keywords/multimodality","display_name":"Multimodality","score":0.46230000257492065}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7900000214576721},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.7820000052452087},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7639999985694885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6072999835014343},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5975000262260437},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5913000106811523},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5892000198364258},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.5866000056266785},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5401999950408936},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.46230000257492065},{"id":"https://openalex.org/C2780660688","wikidata":"https://www.wikidata.org/wiki/Q25052564","display_name":"Multimodal learning","level":2,"score":0.4262000024318695},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3424000144004822},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.34200000762939453},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.31290000677108765},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.28790000081062317},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.21854","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.21854","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.21854","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.21854","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7014485597610474}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"multimodal":[1,53,137],"large":[2],"language":[3],"models":[4,95],"(MLLMs)":[5],"advance":[6],"in":[7,136],"handling":[8],"interleaved":[9],"image-text":[10],"data,":[11],"assessing":[12],"their":[13],"few-shot":[14,35,88,134],"learning":[15],"capabilities":[16,135],"remains":[17],"an":[18],"open":[19],"challenge.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24],"introduce":[25],"FewMMBench,":[26],"a":[27,38,49,127],"comprehensive":[28],"benchmark":[29],"designed":[30],"to":[31,59],"evaluate":[32,75],"MLLMs":[33,78],"under":[34],"conditions,":[36],"with":[37,106],"focus":[39],"on":[40],"In-Context":[41],"Learning":[42],"(ICL)":[43],"and":[44,71,86,114,132],"Chain-of-Thought":[45],"(CoT)":[46],"prompting.":[47],"Covering":[48],"diverse":[50],"suite":[51],"of":[52],"understanding":[54],"tasks,":[55],"from":[56,79],"attribute":[57],"recognition":[58],"temporal":[60],"reasoning,":[61],"FewMMBench":[62,125],"enables":[63],"systematic":[64],"analysis":[65],"across":[66,83],"task":[67],"types,":[68],"model":[69,81],"families,":[70],"prompting":[72],"strategies.":[73],"We":[74],"26":[76],"open-weight":[77],"six":[80],"families":[82],"zero-shot,":[84],"few-shot,":[85],"CoT-augmented":[87],"settings.":[89],"Our":[90],"findings":[91],"reveal":[92],"that":[93],"instruction-tuned":[94],"exhibit":[96],"strong":[97],"zero-shot":[98],"performance":[99],"but":[100],"benefit":[101],"minimally,":[102],"or":[103,109],"even":[104],"regress,":[105],"additional":[107],"demonstrations":[108,113],"CoT":[110],"reasoning.":[111],"Retrieval-based":[112],"increased":[115],"context":[116],"size":[117],"also":[118],"yield":[119],"limited":[120],"gains.":[121],"These":[122],"results":[123],"highlight":[124],"as":[126],"rigorous":[128],"testbed":[129],"for":[130],"diagnosing":[131],"advancing":[133],"LLMs.":[138],"The":[139],"data":[140],"is":[141],"available":[142],"at:":[143],"https://huggingface.co/datasets/mustafaa/FewMMBench":[144]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-27T00:00:00"}