{"id":"https://openalex.org/W7129560946","doi":"https://doi.org/10.48550/arxiv.2602.13764","title":"MOTIF: Learning Action Motifs for Few-shot Cross-Embodiment Transfer","display_name":"MOTIF: Learning Action Motifs for Few-shot Cross-Embodiment Transfer","publication_year":2026,"publication_date":"2026-02-14","ids":{"openalex":"https://openalex.org/W7129560946","doi":"https://doi.org/10.48550/arxiv.2602.13764"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.13764","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.13764","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":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.2602.13764","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124920996","display_name":"Heng Zhi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhi, Heng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126208384","display_name":"Wentao Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Wentao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126248875","display_name":"Lei Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126253543","display_name":"Fengling Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Fengling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126259023","display_name":"Jingjing Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jingjing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126238224","display_name":"Guoli Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Guoli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126255659","display_name":"Heng Tao Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Heng Tao","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":0.20029999315738678,"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":0.20029999315738678,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.15139999985694885,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.14980000257492065,"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/adversarial-system","display_name":"Adversarial system","score":0.6917999982833862},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4675000011920929},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.4458000063896179},{"id":"https://openalex.org/keywords/kinematics","display_name":"Kinematics","score":0.39640000462532043},{"id":"https://openalex.org/keywords/formalism","display_name":"Formalism (music)","score":0.36970001459121704},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.3407000005245209}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7250999808311462},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6917999982833862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5981000065803528},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4675000011920929},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45350000262260437},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.4458000063896179},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.39640000462532043},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37619999051094055},{"id":"https://openalex.org/C73301696","wikidata":"https://www.wikidata.org/wiki/Q5469984","display_name":"Formalism (music)","level":3,"score":0.36970001459121704},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3384000062942505},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.28380000591278076},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2824999988079071},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C166109690","wikidata":"https://www.wikidata.org/wiki/Q4677422","display_name":"Action selection","level":3,"score":0.2685999870300293},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.26269999146461487}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.13764","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.13764","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":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.2602.13764","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.13764","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":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":{"While":[0],"vision-language-action":[1],"(VLA)":[2],"models":[3],"have":[4],"advanced":[5],"generalist":[6],"robotic":[7],"learning,":[8],"cross-embodiment":[9,30,60,94],"transfer":[10,61,145],"remains":[11],"challenging":[12],"due":[13],"to":[14,26,90,109,119],"kinematic":[15],"heterogeneity":[16],"and":[17,45,86,93,130,151],"the":[18,134],"high":[19],"cost":[20],"of":[21,42,136],"collecting":[22],"sufficient":[23],"real-world":[24,131,154],"demonstrations":[25],"support":[27],"fine-tuning.":[28],"Existing":[29],"policies":[31],"typically":[32],"rely":[33],"on":[34,123],"shared-private":[35],"architectures,":[36],"which":[37,138],"suffer":[38],"from":[39,70,106],"limited":[40],"capacity":[41],"private":[43],"parameters":[44],"lack":[46],"explicit":[47],"adaptation":[48],"mechanisms.":[49],"To":[50],"address":[51],"these":[52,104],"limitations,":[53],"we":[54],"introduce":[55],"MOTIF":[56,75],"for":[57],"efficient":[58],"few-shot":[59,144],"that":[62,102],"decouples":[63],"embodiment-agnostic":[64],"spatiotemporal":[65],"patterns,":[66],"termed":[67],"action":[68,72,121],"motifs,":[69],"heterogeneous":[71],"data.":[73],"Specifically,":[74],"first":[76],"learns":[77],"unified":[78],"motifs":[79,105],"via":[80],"vector":[81],"quantization":[82],"with":[83,116],"progress-aware":[84],"alignment":[85],"embodiment":[87],"adversarial":[88],"constraints":[89],"ensure":[91],"temporal":[92],"consistency.":[95],"We":[96],"then":[97],"design":[98],"a":[99,111],"lightweight":[100],"predictor":[101],"predicts":[103],"real-time":[107],"inputs":[108],"guide":[110],"flow-matching":[112],"policy,":[113],"fusing":[114],"them":[115],"robot-specific":[117],"states":[118],"enable":[120],"generation":[122],"new":[124],"embodiments.":[125],"Evaluations":[126],"across":[127],"both":[128],"simulation":[129,150],"environments":[132],"validate":[133],"superiority":[135],"MOTIF,":[137],"significantly":[139],"outperforms":[140],"strong":[141],"baselines":[142],"in":[143,149,153],"scenarios":[146],"by":[147],"6.5%":[148],"43.7%":[152],"settings.":[155],"Code":[156],"is":[157],"available":[158],"at":[159],"https://github.com/buduz/MOTIF.":[160]},"counts_by_year":[],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2026-02-18T00:00:00"}
