{"id":"https://openalex.org/W7135051493","doi":"https://doi.org/10.48550/arxiv.2603.10451","title":"FAR-Dex: Few-shot Data Augmentation and Adaptive Residual Policy Refinement for Dexterous Manipulation","display_name":"FAR-Dex: Few-shot Data Augmentation and Adaptive Residual Policy Refinement for Dexterous Manipulation","publication_year":2026,"publication_date":"2026-03-11","ids":{"openalex":"https://openalex.org/W7135051493","doi":"https://doi.org/10.48550/arxiv.2603.10451"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.10451","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10451","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.2603.10451","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128906586","display_name":"Yushan Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bai, Yushan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126194391","display_name":"Fulin Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Fulin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128848397","display_name":"Hongzheng Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Hongzheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020012572","display_name":"Yuchuang Tong","orcid":"https://orcid.org/0000-0001-8767-1584"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong, Yuchuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128915291","display_name":"En Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, En","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128802631","display_name":"Zhengtao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zhengtao","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":0.9160000085830688,"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":0.9160000085830688,"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":0.030400000512599945,"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/T12290","display_name":"Human Motion and Animation","score":0.010999999940395355,"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/robustness","display_name":"Robustness (evolution)","score":0.696399986743927},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6565999984741211},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5555999875068665},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.43619999289512634},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.4255000054836273},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.3790999948978424},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.34880000352859497}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.696399986743927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6629999876022339},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6565999984741211},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5555999875068665},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5015000104904175},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.43619999289512634},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.4255000054836273},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.4117000102996826},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3790999948978424},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C2775960376","wikidata":"https://www.wikidata.org/wiki/Q1435859","display_name":"Grippers","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32260000705718994},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.3138999938964844},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.30720001459121704},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.29109999537467957},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2705000042915344},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2538999915122986},{"id":"https://openalex.org/C150415221","wikidata":"https://www.wikidata.org/wiki/Q40687","display_name":"Robotic arm","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.10451","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10451","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.2603.10451","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10451","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Achieving":[0],"human-like":[1],"dexterous":[2,61,147],"manipulation":[3,111,148],"through":[4],"the":[5,22,28,66],"collaboration":[6],"of":[7,24,30],"multi-fingered":[8],"hands":[9],"with":[10,49,102,149],"robotic":[11],"arms":[12],"remains":[13],"a":[14,41,77,81],"longstanding":[15],"challenge":[16],"in":[17,60,110,114,142],"robotics,":[18],"primarily":[19],"due":[20],"to":[21,53,69],"scarcity":[23],"high-quality":[25],"demonstrations":[26],"and":[27,56,72,108,117,127],"complexity":[29],"high-dimensional":[31],"action":[32],"spaces.":[33],"To":[34],"address":[35],"these":[36],"challenges,":[37],"we":[38],"propose":[39],"FAR-Dex,":[40],"hierarchical":[42],"framework":[43],"that":[44,94,120],"integrates":[45],"few-shot":[46],"data":[47,82,123],"augmentation":[48],"adaptive":[50,91],"residual":[51,92],"refinement":[52],"enable":[54],"robust":[55],"precise":[57],"arm-hand":[58],"coordination":[59],"tasks.":[62],"First,":[63],"FAR-DexGen":[64],"leverages":[65],"IsaacLab":[67],"simulator":[68],"generate":[70],"diverse":[71],"physically":[73],"constrained":[74],"trajectories":[75],"from":[76],"few":[78],"demonstrations,":[79],"providing":[80],"foundation":[83],"for":[84],"policy":[85],"training.":[86],"Second,":[87],"FAR-DexRes":[88],"introduces":[89],"an":[90],"module":[93],"refines":[95],"policies":[96],"by":[97,125,131],"combining":[98],"multi-step":[99],"trajectory":[100],"segments":[101],"observation":[103],"features,":[104],"thereby":[105],"enhancing":[106],"accuracy":[107],"robustness":[109],"scenarios.":[112],"Experiments":[113],"both":[115],"simulation":[116],"real-world":[118,143],"demonstrate":[119],"FAR-Dex":[121],"improves":[122],"quality":[124],"13.4%":[126],"task":[128],"success":[129,141],"rates":[130],"7%":[132],"over":[133,139],"state-of-the-art":[134],"methods.":[135],"It":[136],"further":[137],"achieves":[138],"80%":[140],"tasks,":[144],"enabling":[145],"fine-grained":[146],"strong":[150],"positional":[151],"generalization.":[152]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-13T00:00:00"}