{"id":"https://openalex.org/W7148799398","doi":"https://doi.org/10.48550/arxiv.2604.01860","title":"Posterior Optimization with Clipped Objective for Bridging Efficiency and Stability in Generative Policy Learning","display_name":"Posterior Optimization with Clipped Objective for Bridging Efficiency and Stability in Generative Policy Learning","publication_year":2026,"publication_date":"2026-04-02","ids":{"openalex":"https://openalex.org/W7148799398","doi":"https://doi.org/10.48550/arxiv.2604.01860"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.01860","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01860","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":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.2604.01860","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132881191","display_name":"Yuhui Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yuhui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132906802","display_name":"Haoran Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088239889","display_name":"Ziyuan Jiang","orcid":"https://orcid.org/0000-0002-5567-5190"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Zhennan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108625272","display_name":"Yuxing Qin","orcid":"https://orcid.org/0009-0006-5442-6789"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Yuxing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014581968","display_name":"Yuxuan Wan","orcid":"https://orcid.org/0000-0002-0192-0058"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Yuxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132868655","display_name":"Weiheng Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Weiheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132921683","display_name":"Dongbin Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Dongbin","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":0.4235999882221222,"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":0.4235999882221222,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.23420000076293945,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.0658000037074089,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.7978000044822693},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.609000027179718},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5600000023841858},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5235999822616577},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.44110000133514404},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.39250001311302185},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.3846000134944916},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.37869998812675476}],"concepts":[{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.7978000044822693},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.661899983882904},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.609000027179718},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5600000023841858},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5554999709129333},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5253999829292297},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5235999822616577},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.44110000133514404},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.39250001311302185},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.37869998812675476},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3483000099658966},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28130000829696655},{"id":"https://openalex.org/C73602740","wikidata":"https://www.wikidata.org/wiki/Q7795822","display_name":"Thompson sampling","level":3,"score":0.2777999937534332},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.01860","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01860","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.01860","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01860","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.4528340697288513,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Expressive":[0],"generative":[1],"models":[2,95],"have":[3],"advanced":[4],"robotic":[5],"manipulation":[6],"by":[7],"capturing":[8],"complex,":[9],"multi-modal":[10],"action":[11,55],"distributions":[12],"over":[13],"temporally":[14],"extended":[15],"trajectories.":[16],"However,":[17],"fine-tuning":[18],"these":[19],"policies":[20],"via":[21],"RL":[22,41],"remains":[23],"challenging":[24],"due":[25],"to":[26,83,91],"instability":[27],"and":[28,86,104,119],"sample":[29],"inefficiency.":[30],"We":[31],"introduce":[32],"Posterior":[33],"Optimization":[34],"with":[35],"Clipped":[36],"Objective":[37],"(POCO),":[38],"a":[39,48,63,121],"principled":[40],"framework":[42],"that":[43,79,110],"formulates":[44],"policy":[45,69,114],"improvement":[46],"as":[47],"posterior":[49,66],"inference":[50],"problem":[51],"tailored":[52],"for":[53],"temporal":[54],"chunks.":[56],"Through":[57],"an":[58,76],"Expectation-Maximization":[59],"procedure,":[60],"POCO":[61,74,111],"distills":[62],"reward-weighted":[64],"implicit":[65],"into":[67],"the":[68],"without":[70,96],"likelihood":[71],"estimation.":[72],"Furthermore,":[73],"adopts":[75],"offline-to-online":[77],"paradigm":[78],"anchors":[80],"online":[81],"exploration":[82],"pre-trained":[84],"priors,":[85],"its":[87],"model-agnostic":[88],"design":[89],"scales":[90],"fine-tune":[92],"large":[93],"VLA":[94],"architectural":[97],"modifications.":[98],"Evaluations":[99],"across":[100],"7":[101],"simulation":[102],"benchmarks":[103],"4":[105],"contact-rich":[106],"real-world":[107,126],"tasks":[108],"demonstrate":[109],"prevents":[112],"catastrophic":[113],"collapse,":[115],"outperforms":[116],"SOTA":[117],"baselines,":[118],"achieves":[120],"96.7%":[122],"success":[123],"rate":[124],"on":[125],"tasks.":[127],"Videos":[128],"are":[129],"available":[130],"at":[131],"our":[132],"project":[133],"website":[134],"https://cccedric.github.io/poco/.":[135]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-04T00:00:00"}
