{"id":"https://openalex.org/W7159666730","doi":"https://doi.org/10.48550/arxiv.2604.27147","title":"How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance","display_name":"How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance","publication_year":2026,"publication_date":"2026-04-29","ids":{"openalex":"https://openalex.org/W7159666730","doi":"https://doi.org/10.48550/arxiv.2604.27147"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.27147","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27147","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,"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.27147","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134929492","display_name":"Jerry Y. Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Jerry Y.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134951381","display_name":"Justin Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Justin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113687340","display_name":"Sheel Shah","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shah, Sheel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134947956","display_name":"Kartik Nair","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nair, Kartik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134955794","display_name":"Nicholas M. Boffi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boffi, Nicholas M.","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.8960000276565552,"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":0.8960000276565552,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.010599999688565731,"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/T12650","display_name":"Aesthetic Perception and Analysis","score":0.007699999958276749,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.5514000058174133},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5446000099182129},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.47749999165534973},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.461899995803833},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4587000012397766},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.44620001316070557},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.38109999895095825}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7222999930381775},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.5514000058174133},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5446000099182129},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4909000098705292},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.47749999165534973},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.461899995803833},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4587000012397766},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.44620001316070557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4189999997615814},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.38109999895095825},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.35519999265670776},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3352999985218048},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.289900004863739},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2720000147819519},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2694999873638153},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.27147","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27147","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,"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.27147","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27147","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,"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"},"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":{"In":[0],"generative":[1],"modeling,":[2],"we":[3,97],"often":[4],"wish":[5],"to":[6,113,148],"produce":[7],"samples":[8],"that":[9,61,71,108],"maximize":[10],"a":[11,23,51,57,104],"user-specified":[12],"reward":[13],"such":[14],"as":[15,26,50,137],"aesthetic":[16],"quality":[17],"or":[18,41,125],"alignment":[19],"with":[20,134],"human":[21],"preferences,":[22],"problem":[24],"known":[25],"\\textit{guidance}.":[27],"Despite":[28],"their":[29],"widespread":[30],"use,":[31],"existing":[32,63],"guidance":[33,49],"methods":[34],"either":[35],"require":[36],"expensive":[37],"multi-particle,":[38],"many-step":[39],"schemes":[40],"rely":[42],"on":[43,94],"poorly":[44],"understood":[45],"approximations.":[46],"We":[47,69],"reformulate":[48],"\\textit{deterministic":[52],"optimal":[53,91],"control":[54],"problem},":[55],"yielding":[56],"hierarchy":[58],"of":[59,77,151],"algorithms":[60],"subsumes":[62],"approaches":[64],"at":[65,141,157],"the":[66,72,90,110,118,152],"coarsest":[67],"level.":[68],"show":[70],"\\textit{flow":[73],"map},":[74],"an":[75,143],"object":[76],"significant":[78],"recent":[79],"interest":[80],"for":[81],"its":[82],"role":[83],"in":[84,89,146],"fast":[85],"inference,":[86],"arises":[87],"naturally":[88],"solution.":[92],"Based":[93],"this":[95],"observation,":[96],"propose":[98],"\\textbf{Flow":[99],"Map":[100],"Reward":[101],"Guidance":[102],"(FMRG)}:":[103],"training-free,":[105],"\\textit{single-trajectory}":[106],"framework":[107],"uses":[109],"flow":[111],"map":[112],"both":[114],"integrate":[115],"and":[116,131],"guide":[117],"flow.":[119],"At":[120],"text-to-image":[121],"scale,":[122],"FMRG":[123],"matches":[124],"surpasses":[126],"baselines":[127],"across":[128],"inverse":[129],"problems":[130],"reward-guided":[132],"generation":[133],"\\textbf{as":[135],"few":[136],"3":[138],"NFEs},":[139],"giving":[140],"least":[142],"order-of-magnitude":[144],"speedup":[145],"comparison":[147],"prior":[149],"state":[150],"art.":[153],"Code":[154],"is":[155],"available":[156],"https://github.com/jrrhuang/fmrg.":[158]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-02T00:00:00"}