{"id":"https://openalex.org/W7154329776","doi":"https://doi.org/10.48550/arxiv.2604.10170","title":"Device-Conditioned Neural Architecture Search for Efficient Robotic Manipulation","display_name":"Device-Conditioned Neural Architecture Search for Efficient Robotic Manipulation","publication_year":2026,"publication_date":"2026-04-11","ids":{"openalex":"https://openalex.org/W7154329776","doi":"https://doi.org/10.48550/arxiv.2604.10170"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.10170","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10170","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.2604.10170","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133623863","display_name":"Yiming Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wu, Yiming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133622091","display_name":"Huan Wang","orcid":"https://orcid.org/0000-0003-4256-021X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Huan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133574880","display_name":"Zhenghao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zhenghao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133608371","display_name":"Ge Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Ge","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133620898","display_name":"Dong Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Dong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5133623863"],"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/T10036","display_name":"Advanced Neural Network Applications","score":0.3573000133037567,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.3573000133037567,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.1599999964237213,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.09690000116825104,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/software-deployment","display_name":"Software deployment","score":0.8586999773979187},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5813000202178955},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.44679999351501465},{"id":"https://openalex.org/keywords/subnet","display_name":"Subnet","score":0.4341999888420105},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4325999915599823},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38600000739097595},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.38600000739097595},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.38109999895095825}],"concepts":[{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.8586999773979187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7109000086784363},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5813000202178955},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.44679999351501465},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4447999894618988},{"id":"https://openalex.org/C21099817","wikidata":"https://www.wikidata.org/wiki/Q7631721","display_name":"Subnet","level":2,"score":0.4341999888420105},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4325999915599823},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4169999957084656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38600000739097595},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.38600000739097595},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.38109999895095825},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.3716000020503998},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.3522000014781952},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.34139999747276306},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3073999881744385},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C150415221","wikidata":"https://www.wikidata.org/wiki/Q40687","display_name":"Robotic arm","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.2531999945640564},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.25279998779296875},{"id":"https://openalex.org/C98025372","wikidata":"https://www.wikidata.org/wiki/Q477538","display_name":"Systems architecture","level":3,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.10170","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10170","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.2604.10170","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10170","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":{"The":[0],"growing":[1],"complexity":[2],"of":[3],"visuomotor":[4],"policies":[5,203],"poses":[6],"significant":[7],"challenges":[8],"for":[9,21,98],"deployment":[10,53,122,129],"with":[11,55,85,179,193],"heterogeneous":[12,124],"robotic":[13,22],"hardware":[14],"constraints.":[15],"However,":[16],"most":[17],"existing":[18],"model-efficient":[19],"approaches":[20],"manipulation":[23,207],"are":[24],"device-":[25],"and":[26,30,60,79,87,126,162,176],"model-specific,":[27],"lack":[28],"generalizability,":[29],"require":[31],"time-consuming":[32],"per-device":[33,92,116],"optimization":[34],"during":[35,148],"the":[36,56],"adaptation":[37],"process.":[38],"In":[39],"this":[40,96],"work,":[41],"we":[42,65,102,138],"propose":[43],"a":[44,67,72,105,194],"unified":[45],"framework":[46],"named":[47],"\\textbf{D}evice-\\textbf{C}onditioned":[48],"\\textbf{Q}uantization-\\textbf{F}or-\\textbf{A}ll":[49],"(DC-QFA)":[50],"which":[51,118],"amortizes":[52],"effort":[54],"device-conditioned":[57],"quantization-aware":[58],"training":[59],"hardware-constrained":[61],"architecture":[62],"search.":[63],"Specifically,":[64],"introduce":[66,140],"single":[68],"supernet":[69],"that":[70,165,199],"spans":[71],"rich":[73],"design":[74],"space":[75],"over":[76],"network":[77],"architectures":[78],"mixed-precision":[80],"bit-widths.":[81],"It":[82],"is":[83],"optimized":[84],"latency-":[86],"memory-aware":[88],"regularization,":[89],"guided":[90],"by":[91],"lookup":[93],"tables.":[94],"With":[95],"supernet,":[97],"each":[99],"target":[100],"platform,":[101],"can":[103],"perform":[104],"once-for-all":[106],"lightweight":[107],"search":[108],"to":[109,144],"select":[110],"an":[111,189],"optimal":[112],"subnet":[113],"without":[114],"any":[115],"re-optimization,":[117],"enables":[119],"more":[120],"generalizable":[121],"across":[123],"hardware,":[125],"substantially":[127],"reduces":[128],"time.":[130],"To":[131],"improve":[132],"long-horizon":[133],"stability":[134],"under":[135,209],"low":[136],"precision,":[137],"further":[139,197],"multi-step":[141],"on-policy":[142],"distillation":[143],"mitigate":[145],"error":[146],"accumulation":[147],"closed-loop":[149],"execution.":[150],"Extensive":[151],"experiments":[152],"on":[153,171,188],"three":[154],"representative":[155],"policy":[156],"backbones,":[157],"such":[158],"as":[159],"DiffusionPolicy-T,":[160],"MDT-V,":[161],"OpenVLA-OFT,":[163],"demonstrate":[164],"our":[166,200],"DC-QFA":[167,202],"achieves":[168],"$2\\text{-}3\\times$":[169],"acceleration":[170],"edge":[172],"devices,":[173],"consumer-grade":[174],"GPUs,":[175],"cloud":[177],"platforms,":[178],"negligible":[180],"performance":[181],"drop":[182],"in":[183],"task":[184],"success.":[185],"Real-world":[186],"evaluations":[187],"Inovo":[190],"robot":[191],"equipped":[192],"force/torque":[195],"sensor":[196],"validates":[198],"low-bit":[201],"maintain":[204],"stable,":[205],"contact-rich":[206],"even":[208],"severe":[210],"quantization.":[211]},"counts_by_year":[],"updated_date":"2026-04-15T06:04:33.058270","created_date":"2026-04-15T00:00:00"}
