{"id":"https://openalex.org/W7166871254","doi":"https://doi.org/10.48550/arxiv.2606.31723","title":"UniTacVLA: Unified Tactile Understanding and Prediction in Vision Language Action Models","display_name":"UniTacVLA: Unified Tactile Understanding and Prediction in Vision Language Action Models","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7166871254","doi":"https://doi.org/10.48550/arxiv.2606.31723"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.31723","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31723","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.2606.31723","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132593483","display_name":"Xidong Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xidong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139846143","display_name":"Yichi Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yichi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139804603","display_name":"Jiaxin Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Jiaxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139753075","display_name":"Fucai Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Fucai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105989284","display_name":"S J Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Siyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068828641","display_name":"Michael Yu Wang","orcid":"https://orcid.org/0000-0002-6524-5741"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Michael Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090578536","display_name":"X . Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Xiaojun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139723460","display_name":"Weihao Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Weihao","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":0.3400999903678894,"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":0.3400999903678894,"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/T10338","display_name":"Advanced Sensor and Energy Harvesting Materials","score":0.20110000669956207,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10914","display_name":"Tactile and Sensory Interactions","score":0.11410000175237656,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5824000239372253},{"id":"https://openalex.org/keywords/tactile-sensor","display_name":"Tactile sensor","score":0.5167999863624573},{"id":"https://openalex.org/keywords/contact-force","display_name":"Contact force","score":0.41530001163482666},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.40310001373291016},{"id":"https://openalex.org/keywords/tactile-stimuli","display_name":"Tactile stimuli","score":0.40119999647140503},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.40049999952316284},{"id":"https://openalex.org/keywords/tactile-perception","display_name":"Tactile perception","score":0.3788999915122986}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6319000124931335},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5824000239372253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5597000122070312},{"id":"https://openalex.org/C46722567","wikidata":"https://www.wikidata.org/wiki/Q7674139","display_name":"Tactile sensor","level":3,"score":0.5167999863624573},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4542999863624573},{"id":"https://openalex.org/C81302111","wikidata":"https://www.wikidata.org/wiki/Q2916417","display_name":"Contact force","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C2987654038","wikidata":"https://www.wikidata.org/wiki/Q859031","display_name":"Tactile stimuli","level":3,"score":0.40119999647140503},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.40049999952316284},{"id":"https://openalex.org/C3017819093","wikidata":"https://www.wikidata.org/wiki/Q328835","display_name":"Tactile perception","level":3,"score":0.3788999915122986},{"id":"https://openalex.org/C28427503","wikidata":"https://www.wikidata.org/wiki/Q13580300","display_name":"Internal model","level":3,"score":0.3366999924182892},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3328999876976013},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3163999915122986},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.2605000138282776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.31723","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31723","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.2606.31723","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31723","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":{"Vision-language-action":[0],"(VLA)":[1],"models":[2,32,73],"have":[3],"achieved":[4],"strong":[5],"performance":[6],"in":[7,15,185],"many":[8],"robotic":[9],"manipulation":[10,71,174],"tasks,":[11,153],"yet":[12],"remain":[13],"limited":[14],"contact-rich":[16,70,152],"dexterous":[17,186],"manipulation.":[18],"To":[19,59],"overcome":[20],"this":[21,60,123],"limitation,":[22],"recent":[23],"vision-tactile-language-action":[24],"(VTLA)":[25],"methods":[26],"incorporate":[27],"tactile":[28,42,53,66,74,91,98,105,111,119,136],"sensing":[29],"into":[30],"VLA":[31],"to":[33,51,138],"provide":[34],"direct":[35],"contact":[36,82,102,177],"information.":[37],"However,":[38],"they":[39],"typically":[40],"treat":[41],"signals":[43,75],"as":[44,76],"passive":[45],"auxiliary":[46],"inputs,":[47],"making":[48],"it":[49],"difficult":[50],"model":[52,96],"semantics":[54],"and":[55,84,94,100,108,117,134,158,163,176],"future":[56,101,110],"physical":[57,187],"interactions.":[58],"end,":[61],"we":[62,87,125],"propose":[63],"a":[64,89,115,127],"unified":[65,90],"learning":[67],"framework":[68],"for":[69,80],"that":[72,131,168],"dynamic":[77],"interaction":[78],"cues":[79],"both":[81,161],"understanding":[83],"prediction.":[85],"Specifically,":[86],"construct":[88],"latent":[92],"space":[93],"jointly":[95],"current":[97],"states":[99],"changes":[103],"through":[104],"chain-of-thought":[106],"reasoning":[107],"coarse-to-fine":[109],"prediction,":[112],"thereby":[113],"forming":[114],"state-aware":[116],"dynamics-aware":[118],"prior.":[120],"Based":[121],"on":[122,148],"prior,":[124],"introduce":[126],"tactile-action":[128],"mixed":[129],"controller":[130],"combines":[132],"real-time":[133],"predicted":[135],"feedback":[137],"refine":[139],"low-frequency":[140],"action":[141],"chunks":[142],"with":[143],"high-frequency":[144],"corrections.":[145],"Real-world":[146],"experiments":[147],"four":[149],"categories":[150],"of":[151],"including":[154],"adjustment,":[155],"insertion,":[156],"wiping,":[157],"assembly,":[159],"under":[160],"clean":[162],"externally":[164],"perturbed":[165],"settings,":[166],"show":[167],"our":[169],"method":[170],"improves":[171],"success":[172],"rate,":[173],"accuracy,":[175],"robustness":[178],"over":[179],"existing":[180],"methods,":[181],"demonstrating":[182],"its":[183],"effectiveness":[184],"interaction.":[188]},"counts_by_year":[],"updated_date":"2026-07-02T06:18:51.028212","created_date":"2026-07-02T00:00:00"}
