{"id":"https://openalex.org/W7166108033","doi":"https://doi.org/10.48550/arxiv.2606.27376","title":"Ask, Solve, Generate: Self-Evolving Unified Multimodal Understanding and Generation via Self-Consistency Rewards","display_name":"Ask, Solve, Generate: Self-Evolving Unified Multimodal Understanding and Generation via Self-Consistency Rewards","publication_year":2026,"publication_date":"2026-06-25","ids":{"openalex":"https://openalex.org/W7166108033","doi":"https://doi.org/10.48550/arxiv.2606.27376"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.27376","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27376","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.2606.27376","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115860474","display_name":"Ritesh Thawkar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thawkar, Ritesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120665300","display_name":"Shravan Venkatraman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Venkatraman, Shravan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134365995","display_name":"Omkar Thawakar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thawakar, Omkar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139450887","display_name":"Abdelrahman Shaker","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shaker, Abdelrahman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139439585","display_name":"Fahad Khan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Fahad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009362997","display_name":"Hisham Cholakkal","orcid":"https://orcid.org/0000-0002-8230-9065"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cholakkal, Hisham","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139408770","display_name":"Salman Khan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Salman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139394009","display_name":"Rao Muhammad Anwer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anwer, Rao Muhammad","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9089999794960022,"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":0.9089999794960022,"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":0.02630000002682209,"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":0.02500000037252903,"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/fidelity","display_name":"Fidelity","score":0.6189000010490417},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.5400000214576721},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5069000124931335},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4896000027656555},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.4661000072956085},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.4050000011920929},{"id":"https://openalex.org/keywords/unified-model","display_name":"Unified Model","score":0.3849000036716461},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.36739999055862427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7791000008583069},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.6189000010490417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5791000127792358},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.5400000214576721},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5069000124931335},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49320000410079956},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4896000027656555},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4661000072956085},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.4050000011920929},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.36739999055862427},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C28427503","wikidata":"https://www.wikidata.org/wiki/Q13580300","display_name":"Internal model","level":3,"score":0.26010000705718994},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.27376","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27376","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.2606.27376","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27376","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Most":[0],"unified":[1,34],"large":[2],"multimodal":[3],"models":[4,219],"(LMMs)":[5],"that":[6,57,63,71,108,127],"support":[7],"both":[8,38],"visual":[9,59,142],"understanding":[10,143,186],"and":[11,65,68,149,163,171,181,207,218],"image":[12,118,210],"generation":[13,147,182,211],"still":[14],"rely":[15],"on":[16,104,205],"curated":[17],"post-training":[18],"supervision,":[19],"such":[20],"as":[21],"human":[22,81],"annotations,":[23,82],"preference":[24,83],"labels,":[25,84],"or":[26,85],"external":[27,87],"reward":[28,161],"models.":[29,89,196],"We":[30,45],"ask":[31],"whether":[32],"a":[33,47,55,61,69,99,122,137,201],"LMM":[35],"can":[36],"improve":[37],"abilities":[39],"autonomously":[40],"using":[41],"only":[42,76,176],"unlabeled":[43],"images.":[44,73],"propose":[46],"self-evolving":[48],"training":[49,152,164],"framework":[50,155],"with":[51,132],"three":[52],"internal":[53,124,151],"roles:":[54],"Proposer":[56],"generates":[58],"questions,":[60],"Solver":[62,95],"answers":[64],"evaluates":[66],"them,":[67],"Generator":[70],"synthesizes":[72],"Training":[74],"uses":[75],"self-derived":[77],"consistency":[78,114],"signals,":[79],"without":[80],"task-trained":[86],"reward/judge":[88],"To":[90],"stabilize":[91],"learning,":[92],"we":[93,120],"introduce":[94],"Token":[96],"Entropy":[97],"(STE),":[98],"continuous":[100],"difficulty":[101],"signal":[102],"based":[103],"token-level":[105],"prediction":[106],"uncertainty":[107],"remains":[109],"useful":[110],"even":[111],"when":[112],"sample-level":[113],"becomes":[115],"unreliable.":[116],"For":[117],"generation,":[119],"design":[121],"multi-scale":[123],"evaluation":[125],"scheme":[126],"combines":[128],"question-answer":[129],"fidelity":[130],"scoring":[131],"cycle-consistent":[133],"captioning.":[134],"This":[135],"creates":[136],"solver-mediated":[138],"coupling,":[139],"where":[140],"better":[141],"enables":[144],"more":[145],"reliable":[146],"assessment":[148],"stronger":[150],"signals.":[153],"The":[154],"preserves":[156],"the":[157,193],"same":[158],"role":[159],"decomposition,":[160],"logic,":[162],"schedule":[165],"across":[166],"diffusion-based":[167],"BLIP3o,":[168],"rectified-flow":[169],"BAGEL,":[170,198],"autoregressive":[172],"VARGPT-v1.1":[173],"architectures,":[174],"requiring":[175],"each":[177],"backbone's":[178],"native":[179],"prompting":[180],"interface.":[183],"Across":[184],"eight":[185],"metrics,":[187],"our":[188],"method":[189],"consistently":[190],"improves":[191,208],"over":[192],"corresponding":[194],"base":[195],"On":[197],"it":[199],"achieves":[200],"$+3.5\\%$":[202],"absolute":[203],"gain":[204],"MMMU":[206],"GenEval":[209],"performance":[212],"from":[213],"$82\\%$":[214],"to":[215],"$85\\%$.":[216],"Code":[217],"are":[220],"publicly":[221],"released.":[222]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-27T00:00:00"}
