{"id":"https://openalex.org/W7147647303","doi":"https://doi.org/10.48550/arxiv.2603.29281","title":"PRISM: A Multi-View Multi-Capability Retail Video Dataset for Embodied Vision-Language Models","display_name":"PRISM: A Multi-View Multi-Capability Retail Video Dataset for Embodied Vision-Language Models","publication_year":2026,"publication_date":"2026-03-31","ids":{"openalex":"https://openalex.org/W7147647303","doi":"https://doi.org/10.48550/arxiv.2603.29281"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.29281","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.29281","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.2603.29281","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132547739","display_name":"Amirreza Rouhi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rouhi, Amirreza","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061448327","display_name":"Parikshit Sakurikar","orcid":"https://orcid.org/0000-0002-9523-5640"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sakurikar, Parikshit","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132558428","display_name":"Satya Sai Reddy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reddy, Satya Sai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132577402","display_name":"Narsimha Menga","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Menga, Narsimha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112174656","display_name":"Anirudh Govil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Govil, Anirudh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132682700","display_name":"Sri Harsha Chittajallu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chittajallu, Sri Harsha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021268829","display_name":"Rajat Aggarwal","orcid":"https://orcid.org/0000-0001-7131-5294"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aggarwal, Rajat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000176044","display_name":"Anoop Namboodiri","orcid":"https://orcid.org/0000-0002-4638-0833"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Namboodiri, Anoop","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5034025990","display_name":"Sashi Reddi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reddi, Sashi","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":0.9077000021934509,"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":0.9077000021934509,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.02539999969303608,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.02319999970495701,"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/embodied-cognition","display_name":"Embodied cognition","score":0.935699999332428},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5849000215530396},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5784000158309937},{"id":"https://openalex.org/keywords/prism","display_name":"Prism","score":0.557699978351593},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.5544999837875366},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5376999974250793},{"id":"https://openalex.org/keywords/affordance","display_name":"Affordance","score":0.45100000500679016},{"id":"https://openalex.org/keywords/endocentric-and-exocentric","display_name":"Endocentric and exocentric","score":0.43950000405311584}],"concepts":[{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.935699999332428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5983999967575073},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5849000215530396},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5784000158309937},{"id":"https://openalex.org/C67666897","wikidata":"https://www.wikidata.org/wiki/Q165896","display_name":"Prism","level":2,"score":0.557699978351593},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.5544999837875366},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5376999974250793},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4675999879837036},{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.45100000500679016},{"id":"https://openalex.org/C131042201","wikidata":"https://www.wikidata.org/wiki/Q493198","display_name":"Endocentric and exocentric","level":4,"score":0.43950000405311584},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4287000000476837},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4016999900341034},{"id":"https://openalex.org/C103683099","wikidata":"https://www.wikidata.org/wiki/Q5370102","display_name":"Embodied agent","level":3,"score":0.40059998631477356},{"id":"https://openalex.org/C2777551103","wikidata":"https://www.wikidata.org/wiki/Q7245680","display_name":"Prism adaptation","level":3,"score":0.3806999921798706},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3756999969482422},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.3319000005722046},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C192327766","wikidata":"https://www.wikidata.org/wiki/Q1038799","display_name":"Cognitive robotics","level":3,"score":0.2872999906539917},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C169087156","wikidata":"https://www.wikidata.org/wiki/Q2131593","display_name":"Framing (construction)","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.29281","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.29281","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.2603.29281","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.29281","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":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.4734284281730652}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"A":[0],"critical":[1],"gap":[2],"exists":[3],"between":[4],"the":[5,15,79,134,186,196,206,217],"general-purpose":[6],"visual":[7,59],"understanding":[8,215],"of":[9,19,57],"state-of-the-art":[10],"physical":[11,51,68,99],"AI":[12,52],"models":[13],"and":[14,70,98,101,124,128,156,163,167,179,241],"specialized":[16],"perceptual":[17],"demands":[18],"structured":[20],"real-world":[21,40,146,236],"deployment":[22,147],"environments.":[23,42],"We":[24],"present":[25],"PRISM,":[26],"a":[27,47,88,144],"270K-sample":[28],"multi-view":[29],"video":[30,177,189],"supervised":[31],"fine-tuning":[32],"(SFT)":[33],"corpus":[34,150],"for":[35,235],"embodied":[36,71,102,213,233],"vision-language-models":[37],"(VLMs)":[38],"in":[39,78,87,212],"retail":[41],"PRISM":[43,84,132,173,194,239],"is":[44,85,133],"motivated":[45],"by":[46,203,220],"simple":[48],"observation":[49],"-":[50,114],"systems":[53],"fail":[54],"not":[55,65],"because":[56,62],"poor":[58],"recognition,":[60],"but":[61],"they":[63],"do":[64],"understand":[66],"space,":[67],"dynamics":[69],"action":[72,103,214],"well":[73],"enough":[74],"to":[75,129,137],"operate":[76],"reliably":[77],"world.":[80],"To":[81],"this":[82],"end,":[83],"grounded":[86],"novel":[89],"three-dimensional":[90],"knowledge":[91,141],"ontology":[92],"that":[93,225],"spans":[94,174],"spatial":[95],"knowledge,":[96,100,131],"temporal":[97],"knowledge.":[104],"It":[105],"covers":[106],"20+":[107,201],"capability":[108],"probes":[109,202],"across":[110,159,199],"four":[111],"evaluation":[112],"dimensions":[113,142],"Embodied":[115],"Reasoning":[116],"(ER),":[117],"Common":[118],"Sense":[119],"(CS),":[120],"Spatial":[121],"Perception":[122],"(SP),":[123],"Intuitive":[125],"Physics":[126],"(IP),":[127],"our":[130],"first":[135],"dataset":[136,240],"instantiate":[138],"all":[139,200],"three":[140],"within":[143],"single":[145],"domain.":[148],"The":[149,238],"captures":[151],"data":[152],"from":[153],"egocentric,":[154],"exocentric":[155],"360\u00b0":[157],"viewpoints":[158],"five":[160],"supermarket":[161],"locations":[162],"includes":[164],"open-ended,":[165],"chain-of-thought,":[166],"multiple-choice":[168],"supervision.":[169],"At":[170],"4":[171],"fps,":[172],"approximately":[175,180],"11.8M":[176],"frames":[178],"730M":[181],"tokens,":[182],"placing":[183],"it":[184],"among":[185],"largest":[187],"domain-specific":[188],"SFT":[190,229],"corpora.":[191],"Fine-tuning":[192],"on":[193],"reduces":[195],"error":[197],"rate":[198],"66.6%":[204],"over":[205],"pre-trained":[207],"baseline,":[208],"with":[209],"significant":[210],"gains":[211],"where":[216],"accuracy":[218],"improves":[219],"36.4%.":[221],"Our":[222],"results":[223],"suggest":[224],"ontology-structured,":[226],"domain":[227],"specific":[228],"can":[230],"meaningfully":[231],"strengthen":[232],"VLMs":[234],"settings.":[237],"more":[242],"details":[243],"are":[244],"available":[245],"at":[246],"https://dreamvu.ai/prism":[247]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-02T00:00:00"}
