{"id":"https://openalex.org/W7160917538","doi":"https://doi.org/10.48550/arxiv.2605.09996","title":"Omni-Persona: Systematic Benchmarking and Improving Omnimodal Personalization","display_name":"Omni-Persona: Systematic Benchmarking and Improving Omnimodal Personalization","publication_year":2026,"publication_date":"2026-05-11","ids":{"openalex":"https://openalex.org/W7160917538","doi":"https://doi.org/10.48550/arxiv.2605.09996"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.09996","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09996","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":"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.2605.09996","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135923731","display_name":"Yeongtak Oh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oh, Yeongtak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135909980","display_name":"Dongwook Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Dongwook","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053487377","display_name":"Sangkwon Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Sangkwon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039955611","display_name":"Heeseung Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Heeseung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135983334","display_name":"Sungroh Yoon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoon, Sungroh","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":0.3635999858379364,"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":0.3635999858379364,"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/T14074","display_name":"Persona Design and Applications","score":0.3237000107765198,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.02710000053048134,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.8077999949455261},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6736000180244446},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6442999839782715},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.6193000078201294},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.4984000027179718},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.45969998836517334},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.45249998569488525},{"id":"https://openalex.org/keywords/verifiable-secret-sharing","display_name":"Verifiable secret sharing","score":0.448199987411499},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.4221999943256378},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4047999978065491}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8077999949455261},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7620999813079834},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6736000180244446},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6442999839782715},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.6193000078201294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5314000248908997},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4984000027179718},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4810999929904938},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.45969998836517334},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.45249998569488525},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.448199987411499},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.4221999943256378},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.3824999928474426},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C168993435","wikidata":"https://www.wikidata.org/wiki/Q6501125","display_name":"Ground","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.31360000371932983},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.28769999742507935},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.27709999680519104},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2612000107765198},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2538999915122986},{"id":"https://openalex.org/C517642484","wikidata":"https://www.wikidata.org/wiki/Q2388514","display_name":"Intelligence analysis","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.09996","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09996","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":"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.2605.09996","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09996","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":"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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"multimodal":[1],"large":[2],"language":[3],"models":[4,114,148],"have":[5],"advanced":[6],"across":[7,75],"text,":[8,25],"image,":[9,26],"and":[10,27,31,71,93,132,146,162,191,216],"audio,":[11],"personalization":[12],"research":[13],"has":[14],"remained":[15],"primarily":[16],"vision-language,":[17],"with":[18,143],"unified":[19,101],"omnimodal":[20,53,211],"benchmarking":[21],"that":[22,121,206],"jointly":[23,89],"covers":[24],"audio":[28],"still":[29],"limited,":[30],"lacking":[32],"the":[33,48,57,63,168,208],"methodological":[34],"rigor":[35],"to":[36],"account":[37],"for":[38,52],"absent-persona":[39,97,144],"scenarios":[40],"or":[41],"systematic":[42],"grounding":[43,81,92,119],"studies.":[44],"We":[45,55],"introduce":[46],"Omni-Persona,":[47],"first":[49],"comprehensive":[50],"benchmark":[51],"personalization.":[54],"formalize":[56],"task":[58,69],"as":[59,157,202],"cross-modal":[60],"routing":[61],"over":[62],"\\emph{Persona":[64],"Modality":[65],"Graph},":[66],"encompassing":[67],"4":[68],"groups":[70],"18":[72],"fine-grained":[73],"tasks":[74],"${\\sim}750$":[76],"items.":[77],"To":[78],"rigorously":[79],"diagnose":[80],"behavior,":[82],"we":[83],"propose":[84],"\\emph{Calibrated":[85],"Accuracy":[86],"($\\mathrm{Cal}$)},":[87],"which":[88],"rewards":[90],"correct":[91],"appropriate":[94],"abstention,":[95],"incorporating":[96],"queries":[98],"within":[99],"a":[100,116,158,203],"evaluation":[102,160],"framework.":[103],"On":[104],"our":[105,196],"dedicated":[106],"experiments,":[107],"three":[108],"diagnostic":[109,204],"findings":[110],"emerge:":[111],"(i)":[112],"open-source":[113],"show":[115],"consistent":[117],"audio-vs-visual":[118],"gap":[120],"RLVR":[122,178],"partially":[123],"narrows":[124],"via":[125],"dense":[126],"rule-based":[127],"supervision;":[128],"(ii)":[129],"answerable":[130],"recall":[131,140],"parameter":[133],"scale":[134],"are":[135],"incomplete":[136],"diagnostics,":[137],"since":[138],"strong":[139],"can":[141],"coexist":[142],"hallucination":[145],"larger":[147],"do":[149],"not":[150],"always":[151],"achieve":[152],"higher":[153],"$\\mathrm{Cal}$,":[154],"exposing":[155],"calibration":[156],"separate":[159],"axis;":[161],"(iii)":[163],"SFT":[164],"is":[165],"bounded":[166],"by":[167],"difficulty":[169],"of":[170,210],"constructing":[171],"annotated":[172],"ground-truth":[173],"supervision":[174],"at":[175],"scale,":[176],"while":[177],"generalizes":[179],"more":[180],"consistently":[181],"through":[182],"outcome-level":[183],"verifiable":[184],"feedback":[185],"yet":[186],"drifts":[187],"toward":[188],"conservative":[189],"behavior":[190],"lower":[192],"generation":[193],"quality":[194],"under":[195],"reward":[197,217],"design.":[198,218],"Omni-Persona":[199],"thus":[200],"serves":[201],"framework":[205],"surfaces":[207],"pitfalls":[209],"personalization,":[212],"guiding":[213],"future":[214],"post-training":[215]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-13T00:00:00"}
