{"id":"https://openalex.org/W4412889753","doi":"https://doi.org/10.18653/v1/2025.acl-long.1454","title":"A Theory of Response Sampling in LLMs: Part Descriptive and Part Prescriptive","display_name":"A Theory of Response Sampling in LLMs: Part Descriptive and Part Prescriptive","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412889753","doi":"https://doi.org/10.18653/v1/2025.acl-long.1454"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.acl-long.1454","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1454","pdf_url":"https://aclanthology.org/2025.acl-long.1454.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.acl-long.1454.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082060797","display_name":"Sarath Sivaprasad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sarath Sivaprasad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035229102","display_name":"Pramod Kaushik","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pramod Kaushik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040674721","display_name":"Sahar Abdelnabi","orcid":"https://orcid.org/0009-0000-5269-951X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sahar Abdelnabi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5003887059","display_name":"Mario Fritz","orcid":"https://orcid.org/0000-0001-8949-9896"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mario Fritz","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":true,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"30091","last_page":"30135"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12705","display_name":"Educational Reforms and Innovations","score":0.29120001196861267,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12705","display_name":"Educational Reforms and Innovations","score":0.29120001196861267,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5116922855377197},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4792487621307373},{"id":"https://openalex.org/keywords/descriptive-statistics","display_name":"Descriptive statistics","score":0.4114491641521454},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3146122992038727},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19599997997283936},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14611008763313293}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5116922855377197},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4792487621307373},{"id":"https://openalex.org/C39896193","wikidata":"https://www.wikidata.org/wiki/Q380344","display_name":"Descriptive statistics","level":2,"score":0.4114491641521454},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3146122992038727},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19599997997283936},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14611008763313293},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.acl-long.1454","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1454","pdf_url":"https://aclanthology.org/2025.acl-long.1454.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.acl-long.1454","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1454","pdf_url":"https://aclanthology.org/2025.acl-long.1454.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412889753.pdf","grobid_xml":"https://content.openalex.org/works/W4412889753.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4240106746","https://openalex.org/W4230369419","https://openalex.org/W3214045955","https://openalex.org/W4242249046","https://openalex.org/W2810115322","https://openalex.org/W2954772049","https://openalex.org/W4387009549","https://openalex.org/W4248686853","https://openalex.org/W4248827146","https://openalex.org/W3214485701"],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"are":[4,102],"increasingly":[5],"utilized":[6],"in":[7,56,79,100,113,125,136,141],"autonomous":[8],"decision-making,":[9],"where":[10],"they":[11],"sample":[12,68],"options":[13],"from":[14,69],"vast":[15],"action":[16],"spaces.However,":[17],"the":[18,57,70,93,109,128],"heuristics":[19,36],"that":[20,33,38,63,97,124],"guide":[21],"this":[22,28,34,64],"sampling":[23,29],"process":[24],"remain":[25],"under-explored.We":[26],"study":[27],"behavior":[30],"and":[31,49,88,117],"show":[32,62],"underlying":[35],"resembles":[37],"of":[39,59,66,111,130],"human":[40,120],"decision-making:":[41],"comprising":[42],"a":[43,50,60,67,74],"descriptive":[44],"component":[45,52,76],"(reflecting":[46],"statistical":[47,71],"norm)":[48],"prescriptive":[51,75,105],"(implicit":[53],"ideal":[54,134],"encoded":[55],"LLM)":[58],"concept.We":[61],"deviation":[65],"norm":[72],"towards":[73],"consistently":[77],"appears":[78],"concepts":[80],"across":[81],"diverse":[82],"real-world":[83,126],"domains":[84],"like":[85],"public":[86],"health,":[87],"economic":[89],"trends.To":[90],"further":[91],"illustrate":[92,123],"theory,":[94],"we":[95,122],"demonstrate":[96],"concept":[98,110],"prototypes":[99],"LLMs":[101],"affected":[103],"by":[104],"norms,":[106],"similar":[107],"to":[108],"normality":[112],"humans.Through":[114],"case":[115],"studies":[116],"comparison":[118],"with":[119],"studies,":[121],"applications,":[127],"shift":[129],"samples":[131],"toward":[132],"an":[133],"value":[135],"LLMs'":[137],"outputs":[138],"can":[139],"result":[140],"significantly":[142],"biased":[143],"decisionmaking,":[144],"raising":[145],"ethical":[146],"concerns.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}