{"id":"https://openalex.org/W7140177344","doi":"https://doi.org/10.48550/arxiv.2603.20236","title":"EnergyAction: Unimanual to Bimanual Composition with Energy-Based Models","display_name":"EnergyAction: Unimanual to Bimanual Composition with Energy-Based Models","publication_year":2026,"publication_date":"2026-03-09","ids":{"openalex":"https://openalex.org/W7140177344","doi":"https://doi.org/10.48550/arxiv.2603.20236"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.20236","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20236","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.20236","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Song, Mingchen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Mingchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Deng, Xiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Wei, Jie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Jiang, Dongmei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Dongmei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Nie, Liqiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie, Liqiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Guan, Weili","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan, Weili","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/T10653","display_name":"Robot Manipulation and Learning","score":0.8127999901771545,"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"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.8127999901771545,"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"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.04600000008940697,"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":0.014399999752640724,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7681999802589417},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.41350001096725464},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.3589000105857849},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.34700000286102295},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.3237000107765198},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.3222000002861023}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7681999802589417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7210000157356262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.536300003528595},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41350001096725464},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32359999418258667},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.31929999589920044},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.25690001249313354}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.20236","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20236","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.20236","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20236","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":"Preprint"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8959506154060364,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2],"unimanual":[3,60,75,97,117,189],"manipulation":[4,28,76],"policies":[5,77,98,118],"have":[6],"achieved":[7],"remarkable":[8],"success":[9],"across":[10],"diverse":[11],"robotic":[12],"tasks":[13,80,202],"through":[14,81,131],"abundant":[15],"training":[16],"data":[17,38],"and":[18,39,101,109,143,200],"well-established":[19],"model":[20,95],"architectures.":[21],"However,":[22],"extending":[23],"these":[24],"capabilities":[25],"to":[26,32,56,78,106,178,191],"bimanual":[27,36,52,79,121,137,192,205],"remains":[29],"challenging":[30],"due":[31],"the":[33,40,82,114,135,167],"lack":[34],"of":[35,42,116,169],"demonstration":[37],"complexity":[41],"coordinating":[43],"dual-arm":[44],"actions.":[45],"Existing":[46],"approaches":[47],"either":[48],"rely":[49],"on":[50,160,197],"extensive":[51],"datasets":[53],"or":[54],"fail":[55],"effectively":[57,187],"leverage":[58,102],"pre-trained":[59],"policies.":[61],"To":[62],"address":[63],"this":[64],"limitation,":[65],"we":[66,94,124,147],"propose":[67,148],"\\textbf{EnergyAction},":[68],"a":[69,120],"novel":[70],"framework":[71],"that":[72,154,185],"compositionally":[73],"transfers":[74,188],"Energy-Based":[83],"Models":[84],"(EBMs).":[85],"Specifically,":[86],"our":[87],"method":[88],"incorporates":[89],"three":[90],"key":[91],"innovations.":[92],"First,":[93],"individual":[96],"as":[99],"EBMs":[100],"their":[103],"compositional":[104],"properties":[105],"compose":[107],"left":[108],"right":[110],"arm":[111],"actions,":[112],"enabling":[113],"fusion":[115],"into":[119],"policy.":[122],"Second,":[123],"introduce":[125],"an":[126],"energy-based":[127],"temporal-spatial":[128],"coordination":[129],"mechanism":[130],"energy":[132],"constraints,":[133],"ensuring":[134],"generated":[136],"actions":[138,171],"are":[139],"both":[140,198],"temporal":[141],"coherence":[142],"spatial":[144],"feasibility.":[145],"Third,":[146],"two":[149],"different":[150],"energy-aware":[151],"denoising":[152,157,180],"strategies":[153,165],"dynamically":[155],"adapt":[156],"steps":[158],"based":[159],"action":[161],"quality":[162],"assessment.":[163],"These":[164],"ensure":[166],"generation":[168],"high-quality":[170],"while":[172],"maintaining":[173],"superior":[174,195],"computational":[175],"efficiency":[176],"compared":[177],"fixed-step":[179],"approaches.":[181],"Experimental":[182],"results":[183],"demonstrate":[184],"EnergyAction":[186],"knowledge":[190],"tasks,":[193],"achieving":[194],"performance":[196],"simulated":[199],"real-world":[201],"with":[203],"minimal":[204],"data.":[206]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-25T00:00:00"}