{"id":"https://openalex.org/W7167629954","doi":"https://doi.org/10.48550/arxiv.2607.04517","title":"VLA Grounder: Language-Conditioning Space Optimization for Black-Box VLA Models","display_name":"VLA Grounder: Language-Conditioning Space Optimization for Black-Box VLA Models","publication_year":2026,"publication_date":"2026-07-05","ids":{"openalex":"https://openalex.org/W7167629954","doi":"https://doi.org/10.48550/arxiv.2607.04517"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.04517","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.04517","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":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.2607.04517","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5095935128","display_name":"Damir Shodiev","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shodiev, Damir","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009170866","display_name":"Aleksei Staroverov","orcid":"https://orcid.org/0000-0002-4730-1543"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Staroverov, Aleksei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115087321","display_name":"Nikita Kachaev","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kachaev, Nikita","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054791318","display_name":"Alexey K. Kovalev","orcid":"https://orcid.org/0000-0003-2180-0990"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kovalev, Alexey K.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140202257","display_name":"Aleksandr I. Panov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Panov, Aleksandr I.","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8234999775886536,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.8234999775886536,"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":0.0714000016450882,"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":0.0430000014603138,"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/space","display_name":"Space (punctuation)","score":0.734000027179718},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7114999890327454},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.7106000185012817},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5896999835968018},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5529000163078308},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.459199994802475}],"concepts":[{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.734000027179718},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7114999890327454},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.7106000185012817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6151999831199646},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5896999835968018},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5529000163078308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49810001254081726},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.459199994802475},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4383000135421753},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3172999918460846},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C2988672794","wikidata":"https://www.wikidata.org/wiki/Q11475","display_name":"Free space","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.04517","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.04517","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":"doi:10.48550/arxiv.2607.04517","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.04517","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":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Vision-Language-Action":[0],"(VLA)":[1],"models":[2],"are":[3],"commonly":[4],"treated":[5],"as":[6,156],"end-to-end":[7],"action":[8,59,130],"policies":[9,48],"conditioned":[10],"on":[11,23,133,144],"natural-language":[12],"task":[13,36],"descriptions.":[14],"In":[15],"practice,":[16],"however,":[17],"their":[18],"behavior":[19,126],"often":[20],"depends":[21],"sharply":[22],"how":[24],"the":[25,107,128],"instruction":[26,72],"is":[27,32,90],"phrased,":[28],"suggesting":[29],"that":[30,68,138,152],"language":[31,54,153],"not":[33],"merely":[34],"a":[35,64,70,74,93,161],"label":[37],"but":[38],"an":[39,157],"optimizable":[40,158],"conditioning":[41],"input.":[42],"We":[43],"study":[44],"whether":[45],"frozen":[46,129],"VLA":[47,109],"can":[49,154],"be":[50],"improved":[51],"by":[52],"optimizing":[53],"space":[55,66,88,116,140],"rather":[56],"than":[57],"updating":[58],"weights.":[60],"Our":[61],"method":[62],"introduces":[63],"language-conditioning":[65,87,115,139],"policy":[67,89],"translates":[69],"human":[71],"into":[73],"short":[75],"VLA-grounded":[76,121],"command":[77],"using":[78],"object":[79],"appearance,":[80],"spatial":[81],"relations,":[82],"and":[83,97,135,147],"target-grounding":[84],"cues.":[85],"The":[86],"initialized":[91],"with":[92,99],"failure-derived":[94],"command-space":[95],"prior":[96],"optimized":[98],"reinforcement":[100],"learning":[101],"from":[102,127],"sparse":[103],"task-completion":[104],"rewards,":[105],"while":[106],"downstream":[108],"remains":[110],"fully":[111],"frozen.":[112],"This":[113],"yields":[114],"optimization:":[117],"RL":[118],"discovers":[119],"which":[120],"commands":[122],"best":[123],"elicit":[124],"successful":[125],"policy.":[131],"Experiments":[132],"RL4VLA":[134],"VL-Think":[136],"show":[137],"optimization":[141],"improves":[142],"success":[143],"instruction-sensitive,":[145],"symbolic,":[146],"multi-object":[148],"manipulation":[149],"tasks,":[150],"demonstrating":[151],"serve":[155],"variable":[159],"for":[160],"robot":[162],"foundation":[163],"models.":[164],"Website:":[165],"https://tttonyalpha.github.io/vla_grounder":[166]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-08T00:00:00"}
