{"id":"https://openalex.org/W7165672164","doi":"https://doi.org/10.48550/arxiv.2606.20961","title":"Is Our Benchmark Enough? An Analysis of Continual Learning for MLLMs","display_name":"Is Our Benchmark Enough? An Analysis of Continual Learning for MLLMs","publication_year":2026,"publication_date":"2026-06-18","ids":{"openalex":"https://openalex.org/W7165672164","doi":"https://doi.org/10.48550/arxiv.2606.20961"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.20961","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20961","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.2606.20961","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139129976","display_name":"Van-Tuan Tran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tran, Van-Tuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081992386","display_name":"Shruthi Gowda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gowda, Shruthi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017603479","display_name":"Merim Dzaferagic","orcid":"https://orcid.org/0000-0003-1254-4163"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dzaferagic, Merim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139163101","display_name":"Marco Ruffini","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruffini, Marco","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.8550000190734863,"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":0.8550000190734863,"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/T11448","display_name":"Face recognition and analysis","score":0.016699999570846558,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.009999999776482582,"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/benchmark","display_name":"Benchmark (surveying)","score":0.8267999887466431},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6970999836921692},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5766000151634216},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.490200012922287},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4848000109195709},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44589999318122864},{"id":"https://openalex.org/keywords/router","display_name":"Router","score":0.43860000371932983},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.4092999994754791}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8267999887466431},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.765500009059906},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6970999836921692},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6252999901771545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5817999839782715},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5766000151634216},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.490200012922287},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4848000109195709},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44589999318122864},{"id":"https://openalex.org/C2775896111","wikidata":"https://www.wikidata.org/wiki/Q642560","display_name":"Router","level":2,"score":0.43860000371932983},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.4092999994754791},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.36640000343322754},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.33219999074935913},{"id":"https://openalex.org/C2775941552","wikidata":"https://www.wikidata.org/wiki/Q25212305","display_name":"Isolation (microbiology)","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.2662000060081482},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2630999982357025}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.20961","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20961","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.2606.20961","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20961","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":[{"id":"https://metadata.un.org/sdg/4","score":0.6178169846534729,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Continual":[0],"adaptation":[1],"is":[2,28],"essential":[3],"for":[4,46,91,158],"multimodal":[5,33],"large":[6],"language":[7],"models":[8],"(MLLMs)":[9],"deployed":[10],"across":[11,134],"evolving":[12],"domains,":[13],"but":[14],"the":[15,22,41,73,141],"state-of-the-art":[16],"MR-LoRA":[17,77],"method":[18,62],"highly":[19],"relies":[20],"on":[21,40],"assumption":[23],"that":[24,99,178],"a":[25,56,128,139,155],"MLLM-based":[26,74],"router":[27,75],"necessary":[29],"to":[30,71,127],"process":[31],"complex":[32],"inputs.":[34],"This":[35,153],"paper":[36],"revisits":[37],"this":[38],"claim":[39],"MLLM-CL":[42],"benchmark":[43,142],"and":[44,68,118,175],"argues":[45],"two":[47,104],"claims.":[48],"\\textbf{First},":[49],"routing":[50,61],"does":[51],"not":[52,87],"require":[53],"an":[54],"MLLM:":[55],"simple":[57],"training-free,":[58],"replay-free":[59],"ptotypical":[60],"(\\textsc{RePRo}),":[63],"uses":[64],"frozen":[65],"pretrained":[66],"features":[67],"task":[69,122,167,170],"prototypes":[70],"match":[72],"of":[76,107,161],"at":[78],"far":[79],"lower":[80],"computational":[81],"cost.":[82],"\\textbf{Second},":[83],"shared":[84],"experts":[85],"do":[86],"improve":[88],"continual":[89,151,162],"learning":[90,145],"MLLMs,":[92],"despite":[93],"their":[94],"theoretical":[95],"appeal.":[96],"We":[97],"show":[98],"these":[100],"findings":[101],"arise":[102],"from":[103],"structural":[105],"limitations":[106],"MLLM-CL:":[108],"(1)":[109],"its":[110,120],"tasks":[111],"are":[112],"\\textbf{highly":[113],"separable}":[114],"in":[115,146],"representation":[116],"space,":[117],"(2)":[119],"fixed":[121],"order":[123],"makes":[124],"conclusions":[125],"\\textbf{sensitive":[126],"single":[129],"curriculum}":[130],"rather":[131,148],"than":[132,149],"robust":[133],"diverse":[135],"continual-learning":[136],"trajectories.":[137],"As":[138],"result,":[140],"primarily":[143],"rewards":[144],"isolation":[147],"genuine":[150],"transfer.":[152],"motivates":[154],"new":[156],"design":[157],"future":[159],"benchmarks":[160],"MLLM":[163],"learning,":[164],"with":[165],"overlapping":[166],"manifolds,":[168],"multiple":[169],"orders,":[171],"fine-grained":[172],"domain":[173],"shifts,":[174],"evaluation":[176],"protocols":[177],"reward":[179],"forward":[180],"transfer":[181],"as":[182,184],"well":[183],"retention.":[185]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}
