{"id":"https://openalex.org/W4321011687","doi":"https://doi.org/10.48550/arxiv.2302.06671","title":"GenAug: Retargeting behaviors to unseen situations via Generative Augmentation","display_name":"GenAug: Retargeting behaviors to unseen situations via Generative Augmentation","publication_year":2023,"publication_date":"2023-02-13","ids":{"openalex":"https://openalex.org/W4321011687","doi":"https://doi.org/10.48550/arxiv.2302.06671"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2302.06671","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.06671","pdf_url":"https://arxiv.org/pdf/2302.06671","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2302.06671","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074803193","display_name":"Zoey Chen","orcid":"https://orcid.org/0000-0001-8020-0704"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zoey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055638286","display_name":"Sho Kiami","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kiami, Sho","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100727390","display_name":"Abhishek Gupta","orcid":"https://orcid.org/0000-0002-2057-826X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gupta, Abhishek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100383672","display_name":"Vikash Kumar","orcid":"https://orcid.org/0000-0002-3168-7955"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kumar, Vikash","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":2,"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":0.9713000059127808,"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":0.9713000059127808,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.951200008392334,"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/T10028","display_name":"Topic Modeling","score":0.9459999799728394,"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/leverage","display_name":"Leverage (statistics)","score":0.7605525255203247},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.755722165107727},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7537901401519775},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7335864305496216},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6710484027862549},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.6310511231422424},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5742886662483215},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5620788335800171},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.5540157556533813},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4527930021286011}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7605525255203247},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.755722165107727},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7537901401519775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7335864305496216},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6710484027862549},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.6310511231422424},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5742886662483215},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5620788335800171},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.5540157556533813},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4527930021286011},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2302.06671","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.06671","pdf_url":"https://arxiv.org/pdf/2302.06671","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2302.06671","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2302.06671","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":"pmh:oai:arXiv.org:2302.06671","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.06671","pdf_url":"https://arxiv.org/pdf/2302.06671","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W4238433571","https://openalex.org/W3174044702","https://openalex.org/W2967848559","https://openalex.org/W4299831724"],"abstract_inverted_index":{"Robot":[0],"learning":[1,32,103],"methods":[2,16],"have":[3],"the":[4,47,99,161,179,192],"potential":[5],"for":[6,124,134],"widespread":[7,109],"generalization":[8,200],"across":[9],"tasks,":[10,159],"environments,":[11],"and":[12,204],"objects.":[13,205],"However,":[14],"these":[15,80,131],"require":[17],"large":[18,64],"diverse":[19],"datasets":[20],"that":[21,56,78,107,145],"are":[22,61],"expensive":[23],"to":[24,33,39,95,148,156,163,166,201],"collect":[25],"in":[26,104,191,199],"real-world":[27,175],"robotics":[28],"settings.":[29],"For":[30],"robot":[31,102],"generalize,":[34],"we":[35,54,113,140],"must":[36],"be":[37],"able":[38,147],"leverage":[40],"sources":[41],"of":[42,66,101,174,181,187],"data":[43,74,127,138],"or":[44],"priors":[45,97],"beyond":[46],"robot's":[48],"own":[49],"experience.":[50],"In":[51,111],"this":[52,182],"work,":[53],"posit":[55],"image-text":[57],"generative":[58,81,117],"models,":[59],"which":[60],"pre-trained":[62,116,132],"on":[63,85,184],"corpora":[65],"web-scraped":[67],"data,":[68,88],"can":[69,90,119],"serve":[70,91,120],"as":[71,92,121],"such":[72],"a":[73,105,142,185,196],"source.":[75],"We":[76,153,177],"show":[77,114],"despite":[79],"models":[82,118,133],"being":[83],"trained":[84],"largely":[86],"non-robotics":[87],"they":[89],"effective":[93,122],"ways":[94],"impart":[96],"into":[98],"process":[100],"way":[106],"enables":[108],"generalization.":[110,152],"particular,":[112],"how":[115],"tools":[123],"semantically":[125],"meaningful":[126],"augmentation.":[128],"By":[129],"leveraging":[130],"generating":[135],"appropriate":[136],"\"semantic\"":[137],"augmentations,":[139],"propose":[141],"system":[143,183],"GenAug":[144,155],"is":[146],"significantly":[149],"improve":[150],"policy":[151],"apply":[154],"tabletop":[157],"manipulation":[158,189],"showing":[160,195],"ability":[162],"re-target":[164],"behavior":[165],"novel":[167,202],"scenarios,":[168],"while":[169],"only":[170],"requiring":[171],"marginal":[172],"amounts":[173],"data.":[176],"demonstrate":[178],"efficacy":[180],"number":[186],"object":[188],"problems":[190],"real":[193],"world,":[194],"40%":[197],"improvement":[198],"scenes":[203]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2023-02-17T00:00:00"}
