{"id":"https://openalex.org/W7163029892","doi":"https://doi.org/10.48550/arxiv.2605.30749","title":"FLAG: Flow Policy MaxEnt-RL by Latent Augmented Guidance","display_name":"FLAG: Flow Policy MaxEnt-RL by Latent Augmented Guidance","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163029892","doi":"https://doi.org/10.48550/arxiv.2605.30749"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30749","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30749","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.30749","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137314112","display_name":"Sungha Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Sungha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042446425","display_name":"Gawon Lee","orcid":"https://orcid.org/0000-0002-8554-9953"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Gawon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014563296","display_name":"Jusuk Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Jusuk","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126730830","display_name":"Jonghae Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Jonghae","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137515088","display_name":"H. Jin Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, H. Jin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5032424238","display_name":"Daesol Cho","orcid":"https://orcid.org/0000-0002-4105-4422"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cho, Daesol","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.3785000145435333,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.3785000145435333,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.16609999537467957,"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":0.08969999849796295,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6237000226974487},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.590499997138977},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5153999924659729},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4571000039577484},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.3919999897480011},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.38199999928474426},{"id":"https://openalex.org/keywords/conditional-entropy","display_name":"Conditional entropy","score":0.3693000078201294},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.35679998993873596},{"id":"https://openalex.org/keywords/control-flow","display_name":"Control flow","score":0.33809998631477356}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6456000208854675},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6237000226974487},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.590499997138977},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5153999924659729},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4952999949455261},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4571000039577484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42669999599456787},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.3919999897480011},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C101721835","wikidata":"https://www.wikidata.org/wiki/Q813908","display_name":"Conditional entropy","level":3,"score":0.3693000078201294},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C160191386","wikidata":"https://www.wikidata.org/wiki/Q868299","display_name":"Control flow","level":2,"score":0.33809998631477356},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.32659998536109924},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.32120001316070557},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.31700000166893005},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.31380000710487366},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.29899999499320984},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2766999900341034},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C2776730729","wikidata":"https://www.wikidata.org/wiki/Q1392130","display_name":"Flag (linear algebra)","level":3,"score":0.2603999972343445},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30749","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30749","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.30749","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30749","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.665858268737793}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Maximum":[0],"entropy":[1],"reinforcement":[2],"learning":[3],"(MaxEnt-RL)":[4],"enables":[5,104],"robust":[6],"exploration,":[7],"yet":[8],"practical":[9],"implementations":[10],"often":[11],"restrict":[12],"policies":[13,23],"to":[14,31,47,114],"simple":[15],"Gaussians.":[16],"While":[17],"recent":[18],"approaches":[19],"incorporate":[20],"expressive":[21,105],"generative":[22],"via":[24],"importance-weighted":[25],"supervised":[26],"learning,":[27],"they":[28],"are":[29],"prone":[30],"importance":[32,62,110],"weight":[33,58],"collapse,":[34],"which":[35],"limits":[36],"their":[37],"scalability":[38],"in":[39],"high-dimensional":[40,115],"action":[41,67],"spaces.":[42],"Our":[43,126],"key":[44],"insight":[45],"is":[46],"mitigate":[48],"this":[49,71],"limitation":[50],"by":[51,61],"localizing":[52],"the":[53,57,65,83],"sampling":[54,63],"region,":[55],"avoiding":[56],"degeneracy":[59],"induced":[60],"over":[64],"entire":[66],"space.":[68],"To":[69],"instantiate":[70],"insight,":[72],"we":[73],"introduce":[74],"\\textbf{FLAG}":[75],"(\\textbf{F}low":[76],"policy":[77,106],"with":[78,86,108],"\\textbf{L}atent-\\textbf{A}ugmented":[79],"\\textbf{G}uidance).":[80],"FLAG":[81,103,119],"augments":[82],"state":[84],"space":[85],"a":[87,93],"flow":[88],"latent":[89],"variable":[90],"and":[91,112],"optimizes":[92],"provably":[94],"consistent":[95],"proxy":[96],"MaxEnt-RL":[97],"objective.":[98],"We":[99],"empirically":[100],"demonstrate":[101],"that":[102],"optimization":[107],"limited":[109],"samples":[111],"scales":[113],"control":[116],"tasks.":[117],"Furthermore,":[118],"achieves":[120],"state-of-the-art":[121],"performance":[122],"across":[123],"challenging":[124],"benchmarks.":[125],"project":[127],"webpage:":[128],"https://flag-rl.github.io/":[129]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-06-02T00:00:00"}