{"id":"https://openalex.org/W7163885169","doi":"https://doi.org/10.48550/arxiv.2606.06614","title":"Re-Centering Humans in LLM Personalization","display_name":"Re-Centering Humans in LLM Personalization","publication_year":2026,"publication_date":"2026-06-04","ids":{"openalex":"https://openalex.org/W7163885169","doi":"https://doi.org/10.48550/arxiv.2606.06614"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.06614","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06614","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.2606.06614","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138135580","display_name":"Lechen Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Lechen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138140090","display_name":"Jiarui Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jiarui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138192236","display_name":"Tal August","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"August, Tal","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/T10028","display_name":"Topic Modeling","score":0.5358999967575073,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.5358999967575073,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.049300000071525574,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12128","display_name":"AI in Service Interactions","score":0.04690000042319298,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.9291999936103821},{"id":"https://openalex.org/keywords/user-modeling","display_name":"User modeling","score":0.4397999942302704},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4185999929904938},{"id":"https://openalex.org/keywords/psychological-intervention","display_name":"Psychological intervention","score":0.36340001225471497},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.35519999265670776},{"id":"https://openalex.org/keywords/human-behavior","display_name":"Human behavior","score":0.298799991607666}],"concepts":[{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.9291999936103821},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.671999990940094},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.4397999942302704},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4185999929904938},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.39309999346733093},{"id":"https://openalex.org/C27415008","wikidata":"https://www.wikidata.org/wiki/Q7256382","display_name":"Psychological intervention","level":2,"score":0.36340001225471497},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32820001244544983},{"id":"https://openalex.org/C117035363","wikidata":"https://www.wikidata.org/wiki/Q3769299","display_name":"Human behavior","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.28220000863075256},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2590999901294708},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.06614","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06614","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.2606.06614","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06614","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":[{"display_name":"Quality Education","score":0.5339116454124451,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Despite":[0],"growing":[1],"interest,":[2],"most":[3],"evaluations":[4],"of":[5,57],"large":[6],"language":[7],"models'":[8],"(LLMs')":[9],"personalization":[10,23,38,135,167],"abilities":[11],"have":[12],"relied":[13],"on":[14,103],"synthetic":[15,42],"data.":[16,45],"It":[17],"remains":[18],"unclear":[19],"how":[20,183],"well":[21],"current":[22],"systems":[24],"work":[25],"for":[26,181],"real":[27],"users.":[28],"In":[29],"this":[30],"paper,":[31],"we":[32,151],"study":[33],"the":[34],"gap":[35],"in":[36,141,147,192],"LLM":[37,120],"performance":[39],"when":[40],"using":[41],"versus":[43],"human":[44,48,83,97,101,139,162],"We":[46,126],"collect":[47],"conversations":[49,63],"(550":[50],"conversations)":[51],"and":[52,73,106,188],"judgments":[53,102,169],"across":[54],"three":[55],"stages":[56],"personalization:":[58],"extracting":[59],"user":[60,190],"attributes":[61,68,76,95],"from":[62,96],"(5,949":[64],"judgments),":[65],"pairing":[66],"relevant":[67,75,104],"with":[69,100,161],"new":[70],"prompts":[71],"(11,919),":[72],"incorporating":[74],"into":[77],"a":[78,179],"personalized":[79,108],"response":[80],"(1,101).":[81],"Incorporating":[82],"data":[84,140,177],"reveals":[85],"system":[86],"limitations":[87],"at":[88],"each":[89],"stage.":[90],"Models":[91],"struggle":[92],"to":[93,138,172],"extract":[94],"conversations,":[98],"disagree":[99],"attributes,":[105],"generate":[107],"responses":[109,117],"that":[110,119,132,153,165,194],"humans":[111,195],"judge":[112],"no":[113],"better":[114],"than":[115],"generic":[116],"(though":[118],"judges":[121],"widely":[122],"rate":[123],"as":[124],"better).":[125],"introduce":[127],"two":[128,144],"lightweight":[129],"training-based":[130],"interventions":[131],"shift":[133],"automated":[134],"evaluation":[136],"closer":[137],"our":[142,148],"first":[143],"stages.":[145],"However,":[146],"third":[149],"stage":[150],"find":[152,196],"learned":[154],"reward":[155],"models":[156,184],"achieve":[157],"only":[158],"modest":[159],"correlation":[160],"ratings,":[163],"suggesting":[164],"human-aligned":[166],"quality":[168],"are":[170],"difficult":[171],"model":[173],"directly.":[174],"Our":[175],"collected":[176],"provides":[178],"foundation":[180],"studying":[182],"should":[185],"extract,":[186],"select,":[187],"incorporate":[189],"information":[191],"ways":[193],"useful.":[197]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-09T00:00:00"}