{"id":"https://openalex.org/W7138143503","doi":"https://doi.org/10.48550/arxiv.2603.14887","title":"ViSA: Visited-State Augmentation for Generalized Goal-Space Contrastive Reinforcement Learning","display_name":"ViSA: Visited-State Augmentation for Generalized Goal-Space Contrastive Reinforcement Learning","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7138143503","doi":"https://doi.org/10.48550/arxiv.2603.14887"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.14887","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14887","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.2603.14887","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071045060","display_name":"Issa Nakamura","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nakamura, Issa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003009172","display_name":"Tomoya Yamanokuchi","orcid":"https://orcid.org/0000-0003-2387-2197"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yamanokuchi, Tomoya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001325713","display_name":"Yuki Kadokawa","orcid":"https://orcid.org/0000-0003-3358-9520"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kadokawa, Yuki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129641442","display_name":"Jia Qu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qu, Jia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129736909","display_name":"Shun Otsub","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Otsub, Shun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129733709","display_name":"Ken Miyamoto","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miyamoto, Ken","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129692174","display_name":"Shotaro Miwa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miwa, Shotaro","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129735918","display_name":"Takamitsu Matsubara","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Matsubara, Takamitsu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"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":0.8626999855041504,"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":0.8626999855041504,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.039400000125169754,"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":0.006500000134110451,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8585000038146973},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7526999711990356},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5375999808311462},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.5235000252723694},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4853000044822693},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4821999967098236},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.43709999322891235},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.43459999561309814}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8585000038146973},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7526999711990356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5978000164031982},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5898000001907349},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5375999808311462},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.5235000252723694},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4853000044822693},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4821999967098236},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.43709999322891235},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.43459999561309814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3734999895095825},{"id":"https://openalex.org/C14646407","wikidata":"https://www.wikidata.org/wiki/Q1430750","display_name":"Bellman equation","level":2,"score":0.35569998621940613},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3264000117778778},{"id":"https://openalex.org/C91873725","wikidata":"https://www.wikidata.org/wiki/Q3445816","display_name":"Function approximation","level":3,"score":0.3264000117778778},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C196340769","wikidata":"https://www.wikidata.org/wiki/Q7698910","display_name":"Temporal difference learning","level":3,"score":0.2635999917984009}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.14887","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14887","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.2603.14887","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14887","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Goal-Conditioned":[0],"Reinforcement":[1,20],"Learning":[2,21],"(GCRL)":[3],"is":[4],"a":[5,9,24,56,77],"framework":[6,25],"for":[7,26,68,82,160],"learning":[8,111],"policy":[10,27],"that":[11],"can":[12,61,165],"reach":[13],"arbitrarily":[14],"given":[15],"goals.":[16,70,162],"In":[17],"particular,":[18],"Contrastive":[19],"(CRL)":[22],"provides":[23],"updates":[28],"using":[29],"an":[30,117],"approximation":[31],"of":[32,90,101,133],"the":[33,52,64,99,125,130,134,169],"value":[34,65,158],"function":[35,66,132],"estimated":[36],"via":[37],"contrastive":[38],"learning,":[39,59],"achieving":[40],"higher":[41],"sample":[42],"efficiency":[43],"compared":[44],"to":[45,123],"conventional":[46],"methods.":[47],"However,":[48],"since":[49],"CRL":[50,83],"treats":[51],"visited":[53],"state":[54,96,104,119],"as":[55,120],"pseudo-goal":[57],"during":[58,106],"it":[60],"accurately":[62],"estimate":[63],"only":[67],"limited":[69],"To":[71],"address":[72],"this":[73],"issue,":[74],"we":[75],"propose":[76],"novel":[78],"data":[79],"augmentation":[80],"approach":[81],"called":[84],"ViSA":[85,88,143],"(Visited-State":[86],"Augmentation).":[87],"consists":[89],"two":[91],"components:":[92],"1)":[93],"generating":[94],"augmented":[95,118],"samples,":[97],"with":[98],"aim":[100],"augmenting":[102],"hard-to-visit":[103,161],"samples":[105],"on-policy":[107],"exploration,":[108],"and":[109,146,150],"2)":[110],"consistent":[112],"embedding":[113,126,135],"space,":[114],"which":[115,155],"uses":[116],"auxiliary":[121],"information":[122],"regularize":[124],"space":[127,136],"by":[128],"reformulating":[129],"objective":[131],"based":[137],"on":[138,168],"mutual":[139],"information.":[140],"We":[141],"evaluate":[142],"in":[144],"simulation":[145],"real-world":[147],"robotic":[148],"tasks":[149],"show":[151],"improved":[152],"goal-space":[153],"generalization,":[154],"permits":[156],"accurate":[157],"estimation":[159],"Further":[163],"details":[164],"be":[166],"found":[167],"project":[170],"page:":[171],"https://issa-n.github.io/projectPage_ViSA/":[172]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-18T00:00:00"}