{"id":"https://openalex.org/W7128034625","doi":"https://doi.org/10.48550/arxiv.2602.05951","title":"Better Source, Better Flow: Learning Condition-Dependent Source Distribution for Flow Matching","display_name":"Better Source, Better Flow: Learning Condition-Dependent Source Distribution for Flow Matching","publication_year":2026,"publication_date":"2026-02-05","ids":{"openalex":"https://openalex.org/W7128034625","doi":"https://doi.org/10.48550/arxiv.2602.05951"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.05951","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/A5125221102","display_name":"Junwan Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kim, Junwan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058108589","display_name":"Jiho Park","orcid":"https://orcid.org/0000-0002-1048-3881"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Jiho","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125099679","display_name":"Seonghu Jeon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeon, Seonghu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125102031","display_name":"Seungryong Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Seungryong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5125221102"],"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9437000155448914,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9437000155448914,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.01140000019222498,"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":0.0024999999441206455,"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/matching","display_name":"Matching (statistics)","score":0.5888000130653381},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5023000240325928},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.484499990940094},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4839000105857849},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.47429999709129333},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4481000006198883},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4250999987125397},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.41999998688697815},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3801000118255615}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.619700014591217},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5888000130653381},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5023000240325928},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4839000105857849},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.47429999709129333},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.47099998593330383},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4481000006198883},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4250999987125397},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.41999998688697815},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3801000118255615},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3799000084400177},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35420000553131104},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.35359999537467957},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3368000090122223},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.296099990606308},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27160000801086426},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2653999924659729},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25619998574256897},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.05951","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.2602.05951","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.05951","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.2602.05951","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Flow":[0],"matching":[1,90,149],"has":[2],"recently":[3],"emerged":[4],"as":[5,47],"a":[6,30,34,84,176,187],"promising":[7],"alternative":[8],"to":[9,175],"diffusion-based":[10],"generative":[11],"models,":[12,39],"particularly":[13],"for":[14,132,192],"text-to-image":[15,78,166],"generation.":[16],"Despite":[17],"its":[18],"flexibility":[19],"in":[20,51,155,180],"allowing":[21],"arbitrary":[22],"source":[23,44,64,86,127,189],"distributions,":[24],"most":[25,160],"existing":[26],"approaches":[27],"rely":[28],"on":[29],"standard":[31],"Gaussian":[32],"distribution,":[33],"choice":[35,142],"inherited":[36],"from":[37],"diffusion":[38],"and":[40,115,117,123,128,134,170],"rarely":[41],"consider":[42],"the":[43,63,74,110,141,183],"distribution":[45,65,87,190],"itself":[46],"an":[48],"optimization":[49],"target":[50,129,144],"such":[52,157],"settings.":[53],"In":[54],"this":[55],"work,":[56],"we":[57,81],"show":[58,118],"that":[59,92,103,119],"principled":[60,188],"design":[61,191],"of":[62,76,143,186],"is":[66],"not":[67],"only":[68],"feasible":[69],"but":[70],"also":[71],"beneficial":[72],"at":[73],"scale":[75],"modern":[77],"systems.":[79],"Specifically,":[80],"propose":[82],"learning":[83],"condition-dependent":[85],"under":[88],"flow":[89,148,194],"objective":[91],"better":[93],"exploit":[94],"rich":[95],"conditioning":[96,108],"signals.":[97],"We":[98,137],"identify":[99],"key":[100],"failure":[101],"modes":[102],"arise":[104],"when":[105],"directly":[106],"incorporating":[107],"into":[109],"source,":[111],"including":[112,173],"distributional":[113],"collapse":[114],"instability,":[116],"appropriate":[120],"variance":[121],"regularization":[122],"directional":[124],"alignment":[125],"between":[126],"are":[130,159],"critical":[131],"stable":[133],"effective":[135],"learning.":[136],"further":[138],"analyze":[139],"how":[140],"representation":[145],"space":[146],"impacts":[147],"with":[150],"structured":[151],"sources,":[152],"revealing":[153],"regimes":[154],"which":[156],"designs":[158],"effective.":[161],"Extensive":[162],"experiments":[163],"across":[164],"multiple":[165],"benchmarks":[167],"demonstrate":[168],"consistent":[169],"robust":[171],"improvements,":[172],"up":[174],"3x":[177],"faster":[178],"convergence":[179],"FID,":[181],"highlighting":[182],"practical":[184],"benefits":[185],"conditional":[193],"matching.":[195]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-07T00:00:00"}