{"id":"https://openalex.org/W7155073560","doi":"https://doi.org/10.48550/arxiv.2604.17968","title":"From Fallback to Frontline: When Can LLMs be Superior Annotators of Human Perspectives?","display_name":"From Fallback to Frontline: When Can LLMs be Superior Annotators of Human Perspectives?","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155073560","doi":"https://doi.org/10.48550/arxiv.2604.17968"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.17968","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17968","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.2604.17968","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134156798","display_name":"Hasan Amin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Amin, Hasan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120026643","display_name":"Harry Yizhou Tian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian, Harry Yizhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085545446","display_name":"Xiaoni Duan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duan, Xiaoni","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134212154","display_name":"Chien-Ju Ho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ho, Chien-Ju","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124335891","display_name":"Rajiv Khanna","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khanna, Rajiv","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134204429","display_name":"Ming Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Ming","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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.10840000212192535,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.10840000212192535,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.060100000351667404,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.05180000141263008,"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/framing","display_name":"Framing (construction)","score":0.7365999817848206},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4275999963283539},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.3986999988555908},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.36079999804496765},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.33959999680519104},{"id":"https://openalex.org/keywords/compromise","display_name":"Compromise","score":0.3012999892234802}],"concepts":[{"id":"https://openalex.org/C169087156","wikidata":"https://www.wikidata.org/wiki/Q2131593","display_name":"Framing (construction)","level":2,"score":0.7365999817848206},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4275999963283539},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.3986999988555908},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.38100001215934753},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3668000102043152},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.36079999804496765},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.33959999680519104},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.3244999945163727},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.31690001487731934},{"id":"https://openalex.org/C46355384","wikidata":"https://www.wikidata.org/wiki/Q726686","display_name":"Compromise","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.298799991607666},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C2993724205","wikidata":"https://www.wikidata.org/wiki/Q315","display_name":"Human language","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.2680000066757202},{"id":"https://openalex.org/C151913843","wikidata":"https://www.wikidata.org/wiki/Q3454555","display_name":"Dominance (genetics)","level":3,"score":0.2542000114917755},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.17968","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17968","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.2604.17968","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17968","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":{"Although":[0],"large":[1],"language":[2],"models":[3],"(LLMs)":[4],"are":[5,13,72],"increasingly":[6],"used":[7],"as":[8,16,36,84,112,117,119],"annotators":[9],"at":[10],"scale,":[11],"they":[12],"typically":[14],"treated":[15],"a":[17,22,40,132,136],"pragmatic":[18],"fallback":[19],"rather":[20,97],"than":[21,98],"faithful":[23],"estimator":[24],"of":[25,39,82,101],"human":[26,54,123,142],"perspectives.":[27,143],"This":[28,76],"work":[29],"challenges":[30],"that":[31,69],"presumption.":[32],"By":[33],"framing":[34],"perspective-taking":[35],"the":[37,46],"estimation":[38],"latent":[41],"group-level":[42],"judgment,":[43],"we":[44],"characterize":[45],"conditions":[47,71],"under":[48],"which":[49],"modern":[50],"LLMs":[51,83,110,130],"can":[52],"outperform":[53],"annotators,":[55],"including":[56,86],"in-group":[57],"humans,":[58],"when":[59],"predicting":[60],"aggregate":[61],"subgroup":[62],"opinions":[63],"on":[64],"subjective":[65],"tasks,":[66],"and":[67,89,94],"show":[68],"these":[70],"common":[73],"in":[74],"practice.":[75],"advantage":[77],"arises":[78],"from":[79,131],"structural":[80],"properties":[81],"estimators,":[85,116],"low":[87],"variance":[88],"reduced":[90],"coupling":[91],"between":[92],"representation":[93],"processing":[95],"biases,":[96],"any":[99],"claim":[100],"lived":[102],"experience.":[103],"Our":[104],"analysis":[105],"identifies":[106],"clear":[107],"regimes":[108],"where":[109,122],"act":[111],"statistically":[113],"superior":[114],"frontline":[115],"well":[118],"principled":[120,137],"limits":[121],"judgment":[124],"remains":[125],"essential.":[126],"These":[127],"findings":[128],"reposition":[129],"cost-saving":[133],"compromise":[134],"to":[135],"tool":[138],"for":[139],"estimating":[140],"collective":[141]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-22T00:00:00"}
