{"id":"https://openalex.org/W4412944773","doi":"https://doi.org/10.18653/v1/2025.acl-long.1118","title":"Towards Harmonized Uncertainty Estimation for Large Language Models","display_name":"Towards Harmonized Uncertainty Estimation for Large Language Models","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412944773","doi":"https://doi.org/10.18653/v1/2025.acl-long.1118"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.acl-long.1118","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1118","pdf_url":"https://aclanthology.org/2025.acl-long.1118.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":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.acl-long.1118.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100448625","display_name":"Rui Li","orcid":"https://orcid.org/0000-0003-2281-6062"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rui Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087663864","display_name":"Jing Long","orcid":"https://orcid.org/0000-0002-5597-721X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jing Long","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039750147","display_name":"Manzhi Qi","orcid":"https://orcid.org/0009-0001-0721-0081"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Muge Qi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Heming Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heming Xia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101013822","display_name":"Sha Lei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Sha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Peiyi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peiyi Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5110285832","display_name":"Zhifang Sui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhifang Sui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08849418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"22938","last_page":"22953"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9402999877929688,"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":0.9402999877929688,"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/computer-science","display_name":"Computer science","score":0.6635030508041382},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5708012580871582},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3258066475391388},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1304410994052887},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11946412920951843},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.11737173795700073}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6635030508041382},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5708012580871582},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3258066475391388},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1304410994052887},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11946412920951843},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.11737173795700073}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.acl-long.1118","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1118","pdf_url":"https://aclanthology.org/2025.acl-long.1118.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.1118","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1118","pdf_url":"https://aclanthology.org/2025.acl-long.1118.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":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412944773.pdf","grobid_xml":"https://content.openalex.org/works/W4412944773.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"To":[0],"facilitate":[1],"robust":[2],"and":[3,35,61,109],"trustworthy":[4],"deployment":[5],"of":[6,18,38,50,118],"large":[7],"language":[8],"models":[9,108],"(LLMs),":[10],"it":[11],"is":[12],"essential":[13],"to":[14,40,53,101,120],"quantify":[15],"the":[16,32,48,97],"reliability":[17],"their":[19,65],"generations":[20],"through":[21],"uncertainty":[22,42,70,103],"estimation.While":[23],"recent":[24],"efforts":[25],"have":[26],"made":[27],"significant":[28],"advancements":[29],"by":[30],"leveraging":[31],"internal":[33],"logic":[34],"linguistic":[36],"features":[37],"LLMs":[39],"estimate":[41],"scores,":[43],"our":[44],"empirical":[45],"analysis":[46],"highlights":[47],"pitfalls":[49],"these":[51],"methods":[52],"strike":[54],"a":[55,89],"harmonized":[56],"estimation":[57],"between":[58],"indication,":[59],"balance,":[60],"calibration,":[62],"which":[63,114],"hinders":[64],"broader":[66],"capability":[67],"for":[68,79],"accurate":[69],"estimation.To":[71],"address":[72],"this":[73],"challenge,":[74],"we":[75],"propose":[76],"CUE":[77],"(Corrector":[78],"Uncertainty":[80],"Estimation):":[81],"A":[82],"straightforward":[83],"yet":[84],"effective":[85],"method":[86],"that":[87],"employs":[88],"lightweight":[90],"model":[91],"trained":[92],"on":[93],"data":[94],"aligned":[95],"with":[96],"target":[98],"LLM's":[99],"performance":[100],"adjust":[102],"scores.Comprehensive":[104],"experiments":[105],"across":[106],"diverse":[107],"tasks":[110],"demonstrate":[111],"its":[112],"effectiveness,":[113],"achieves":[115],"consistent":[116],"improvements":[117],"up":[119],"60%":[121],"over":[122],"existing":[123],"methods.":[124]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}