{"id":"https://openalex.org/W7164022596","doi":"https://doi.org/10.48550/arxiv.2606.08881","title":"Benchmarking Vision-Language-Action Models on SO-101: Failure and Recovery Analysis","display_name":"Benchmarking Vision-Language-Action Models on SO-101: Failure and Recovery Analysis","publication_year":2026,"publication_date":"2026-06-07","ids":{"openalex":"https://openalex.org/W7164022596","doi":"https://doi.org/10.48550/arxiv.2606.08881"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.08881","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08881","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.2606.08881","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138216430","display_name":"Yi Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138241297","display_name":"Xinchuan Qiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Xinchuan","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":0.2379000037908554,"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":0.2379000037908554,"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":0.16120000183582306,"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":0.15279999375343323,"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/benchmark","display_name":"Benchmark (surveying)","score":0.7853000164031982},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.7204999923706055},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6614999771118164},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.6215000152587891},{"id":"https://openalex.org/keywords/teleoperation","display_name":"Teleoperation","score":0.6129999756813049},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5139999985694885},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.44350001215934753}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7853000164031982},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7204999923706055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6711999773979187},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6614999771118164},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6215000152587891},{"id":"https://openalex.org/C161759796","wikidata":"https://www.wikidata.org/wiki/Q3982902","display_name":"Teleoperation","level":3,"score":0.6129999756813049},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5644999742507935},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5139999985694885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4683000147342682},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.3813000023365021},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.31869998574256897},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.2775999903678894}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.08881","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08881","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.2606.08881","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08881","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],"have":[3],"demonstrated":[4],"strong":[5],"generalization":[6],"in":[7,16],"robotic":[8,21,50,134,181],"manipulation,":[9],"yet":[10],"existing":[11],"evaluations":[12],"are":[13],"primarily":[14],"conducted":[15],"simulation":[17],"or":[18],"on":[19,26,46,84],"expensive":[20],"platforms,":[22],"leaving":[23],"their":[24],"robustness":[25],"affordable":[27],"real-world":[28,36,71],"robots":[29],"largely":[30],"unexplored.":[31],"We":[32],"present":[33],"a":[34,96,170],"standardized":[35],"benchmark":[37,53,94,172],"for":[38,173],"evaluating":[39,174],"representative":[40,56],"VLA":[41,119],"and":[42,76,81,101,105,159,166],"imitation":[43,124],"learning":[44,125],"policies":[45,120],"the":[47,85,93,123,141,155],"low-cost":[48,133,180],"SO-101":[49,168],"platform.":[51,87],"The":[52],"comprises":[54],"four":[55],"manipulation":[57],"tasks":[58],"together":[59],"with":[60],"unified":[61],"evaluation":[62,107],"protocols,":[63],"enabling":[64],"systematic":[65],"comparison":[66],"under":[67,132,178],"embodiment":[68],"uncertainty.":[69],"Using":[70],"teleoperated":[72],"demonstrations,":[73],"we":[74],"fine-tune":[75],"evaluate":[77],"$\u03c0_{0.5}$,":[78],"SmolVLA,":[79],"Wall-X,":[80],"ACT":[82],"directly":[83],"physical":[86],"Beyond":[88],"conventional":[89],"task":[90,164],"success":[91,165],"rates,":[92],"incorporates":[95],"structured":[97],"failure":[98,103,143,158],"taxonomy,":[99],"semantic-":[100],"execution-level":[102],"decomposition,":[104],"recovery-aware":[106],"metrics":[108],"to":[109],"characterize":[110],"policy":[111],"robustness.":[112],"Experimental":[113],"results":[114,153],"show":[115],"that":[116],"stronger":[117],"pretrained":[118],"generally":[121],"outperform":[122],"baseline,":[126],"although":[127],"performance":[128],"remains":[129],"highly":[130],"task-dependent":[131],"deployment":[135,182],"conditions.":[136,183],"Execution":[137],"instability":[138],"emerges":[139],"as":[140,169],"dominant":[142],"source,":[144],"while":[145],"recovery":[146,160],"capability":[147],"varies":[148],"substantially":[149],"across":[150],"architectures.":[151],"These":[152],"highlight":[154],"importance":[156],"of":[157],"analysis":[161],"beyond":[162],"binary":[163],"establish":[167],"practical":[171],"embodied":[175],"AI":[176],"systems":[177],"realistic":[179]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-10T00:00:00"}