{"id":"https://openalex.org/W7204928770","doi":"https://doi.org/10.48550/arxiv.2608.29107","title":"PathGuide: Dynamic Classifier-Free Guidance via On-Policy Transport Alignment","display_name":"PathGuide: Dynamic Classifier-Free Guidance via On-Policy Transport Alignment","publication_year":2026,"publication_date":"2026-08-29","ids":{"openalex":"https://openalex.org/W7204928770","doi":"https://doi.org/10.48550/arxiv.2608.29107"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2608.29107","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.29107","pdf_url":"https://arxiv.org/pdf/2608.29107","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.29107","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5148931171","display_name":"Avishag Nevo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Nevo, Avishag","raw_affiliation_strings":["Technion -Israel Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technion -Israel Institute of Technology","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000106487","display_name":"Tamir Hazan","orcid":"https://orcid.org/0000-0003-1652-3845","observed_orcids":["https://orcid.org/0000-0003-1652-3845"]},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Hazan, Tamir","raw_affiliation_strings":["Technion -Israel Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technion -Israel Institute of Technology","institution_ids":["https://openalex.org/I174306211"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I174306211"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"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":0.9761000275611877,"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":0.9761000275611877,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.006000000052154064,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.003599999938160181,"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/classifier-free-guidance","display_name":"classifier-free guidance","score":0.9909999966621399},{"id":"https://openalex.org/keywords/flow-based-generative-models","display_name":"flow-based generative models","score":0.7680000066757202},{"id":"https://openalex.org/keywords/conditional-generation","display_name":"conditional generation","score":0.5490000247955322},{"id":"https://openalex.org/keywords/path-optimization","display_name":"path optimization","score":0.5040000081062317},{"id":"https://openalex.org/keywords/continuity-equation","display_name":"continuity equation","score":0.8740000128746033},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"adaptive sampling","score":0.49000000953674316},{"id":"https://openalex.org/keywords/image-generation","display_name":"image generation","score":0.3409999907016754}],"concepts":[{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.5740000009536743},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.560699999332428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5012999773025513},{"id":"https://openalex.org/C110521144","wikidata":"https://www.wikidata.org/wiki/Q193460","display_name":"Scalar field","level":2,"score":0.45509999990463257},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.4496999979019165},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.43299999833106995},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.427700012922287},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.42750000953674316},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.4205999970436096},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3995000123977661},{"id":"https://openalex.org/C91188154","wikidata":"https://www.wikidata.org/wiki/Q186247","display_name":"Vector field","level":2,"score":0.39340001344680786},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38920000195503235},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3792000114917755},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3765000104904175},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C201004817","wikidata":"https://www.wikidata.org/wiki/Q1707071","display_name":"Guidance system","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.2930999994277954},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.2784999907016754},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.27549999952316284}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.29107","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.29107","pdf_url":"https://arxiv.org/pdf/2608.29107","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.29107","doi":"https://doi.org/10.48550/arxiv.2608.29107","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.29107","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2608.29107","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.29107","pdf_url":"https://arxiv.org/pdf/2608.29107","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204928770.pdf","grobid_xml":"https://content.openalex.org/works/W7204928770.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W2052104757","https://openalex.org/W2068039185","https://openalex.org/W2112796928","https://openalex.org/W2734498959","https://openalex.org/W2765449478","https://openalex.org/W2964121744","https://openalex.org/W3162926177","https://openalex.org/W4297676498","https://openalex.org/W4387995353","https://openalex.org/W4402696791","https://openalex.org/W4405917844","https://openalex.org/W4409346780","https://openalex.org/W4417125262","https://openalex.org/W6893755354","https://openalex.org/W7087532664","https://openalex.org/W7126188617"],"related_works":["https://openalex.org/W7160619357","https://openalex.org/W7214031476","https://openalex.org/W7126188617","https://openalex.org/W4388963769","https://openalex.org/W7160843501","https://openalex.org/W7221823116","https://openalex.org/W7221520068","https://openalex.org/W7159666730","https://openalex.org/W7131396889","https://openalex.org/W4414586120"],"abstract_inverted_index":{"While":[0],"modern":[1],"generative":[2],"models":[3],"excel":[4],"at":[5],"modeling":[6],"complex":[7],"data,":[8],"precise":[9],"inference-time":[10],"control":[11],"in":[12],"conditional":[13,109,122],"generation":[14,156],"remains":[15],"a":[16,23,35,59,66,88,92,130,161],"critical":[17],"challenge.":[18],"Classifier-free":[19],"guidance":[20,44,57,147,198],"(CFG)":[21],"is":[22,31,103],"primary":[24],"mechanism":[25],"for":[26,140],"such":[27],"control,":[28],"yet":[29],"it":[30],"typically":[32],"treated":[33],"as":[34,73,160],"static":[36],"tuning":[37],"parameter.":[38],"In":[39],"flow-based":[40],"models,":[41],"however,":[42],"the":[43,48,52,79,83,100,107,112,115,120],"scale":[45],"fundamentally":[46],"dictates":[47],"velocity":[49],"field":[50,102,110],"and":[51,152,173,189,195],"resulting":[53],"probability":[54],"path,":[55],"making":[56],"selection":[58,72,89],"dynamic":[60],"path-optimization":[61],"problem.":[62,77],"We":[63,165],"introduce":[64],"PathGuide,":[65],"framework":[67],"that":[68,98,182],"reformulates":[69],"scalar":[70,125],"CFG":[71],"an":[74,136],"on-policy":[75],"transport":[76],"Leveraging":[78],"weak":[80],"form":[81],"of":[82],"continuity":[84],"equation,":[85],"we":[86,96],"derive":[87],"criterion":[90,128],"with":[91,119,135],"direct":[93],"path-correctness":[94],"interpretation:":[95],"prove":[97],"if":[99],"guided":[101],"weakly":[104],"equivalent":[105],"to":[106,149],"exact":[108],"along":[111],"generated":[113],"rollout,":[114],"sampler's":[116],"path":[117,187],"coincides":[118],"target":[121],"law.":[123],"For":[124],"CFG,":[126],"this":[127,183],"yields":[129],"strictly":[131],"quadratic":[132],"local":[133],"objective":[134],"efficient,":[137],"closed-form":[138],"selector":[139,185],"each":[141],"solver":[142],"interval.":[143],"PathGuide":[144],"enables":[145],"optimal":[146],"scales":[148],"be":[150],"computed":[151],"used":[153],"online":[154],"during":[155],"or":[157],"fitted":[158],"offline":[159],"reusable":[162],"piecewise-constant":[163],"schedule.":[164],"validate":[166],"our":[167],"method":[168],"on":[169],"low-resolution":[170],"image":[171],"manifolds":[172],"controlled":[174],"settings":[175],"across":[176],"various":[177],"continuous-time":[178],"flow":[179],"constructions,":[180],"demonstrating":[181],"transport-based":[184],"improves":[186],"alignment":[188],"sample":[190],"fidelity":[191],"over":[192],"both":[193],"fixed":[194],"state-of-the-art":[196],"adaptive":[197],"baselines.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-02T00:00:00"}
