{"id":"https://openalex.org/W7166816797","doi":"https://doi.org/10.18653/v1/2026.findings-acl.490","title":"LLM Prompt Duel Optimizer: Efficient Label-Free Prompt Optimization","display_name":"LLM Prompt Duel Optimizer: Efficient Label-Free Prompt Optimization","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166816797","doi":"https://doi.org/10.18653/v1/2026.findings-acl.490"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.490","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.490","pdf_url":"https://aclanthology.org/2026.findings-acl.490.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.490.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139720480","display_name":"Yuanchen Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuanchen Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139744828","display_name":"Saurabh Verma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saurabh Verma","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100637871","display_name":"Justin Lee","orcid":"https://orcid.org/0000-0002-3657-4386"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Justin Lee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056039500","display_name":"Fangzhou Xiong","orcid":"https://orcid.org/0000-0002-2592-4096"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fangzhou Xiong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139849357","display_name":"Poppy Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Poppy Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139718966","display_name":"Amel Awadelkarim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Amel Awadelkarim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139736822","display_name":"Xu Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101564744","display_name":"Yubai Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yubai Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139824652","display_name":"Shawndra Hill","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shawndra Hill","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":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.86178898,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"10066","last_page":"10089"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.051500000059604645,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.051500000059604645,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.042399998754262924,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11034","display_name":"Digital Filter Design and Implementation","score":0.039400000125169754,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/process","display_name":"Process (computing)","score":0.29760000109672546},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.24889999628067017},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.2476000040769577},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.24279999732971191},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.23989999294281006}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.492900013923645},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28049999475479126},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26409998536109924},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.24889999628067017},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2476000040769577},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.24279999732971191},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.23989999294281006},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.23819999396800995},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.23749999701976776}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.490","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.490","pdf_url":"https://aclanthology.org/2026.findings-acl.490.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-acl.490","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.490","pdf_url":"https://aclanthology.org/2026.findings-acl.490.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":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166816797.pdf","grobid_xml":"https://content.openalex.org/works/W7166816797.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"are":[4,26],"highly":[5],"sensitive":[6],"to":[7,18,28,65,79],"prompts,":[8],"but":[9],"most":[10],"automatic":[11],"prompt":[12,41,53],"optimization":[13,42],"(APO)":[14],"methods":[15],"assume":[16],"access":[17],"ground-truth":[19],"references":[20],"(e.g.,":[21],"labeled":[22],"validation":[23],"data)":[24],"that":[25,96],"costly":[27],"obtain.We":[29],"propose":[30],"the":[31,81],"Prompt":[32],"Duel":[33],"Optimizer":[34],"(PDO),":[35],"a":[36,56,70],"sampleefficient":[37],"framework":[38],"for":[39],"label-free":[40,103],"based":[43],"on":[44,88],"pairwise":[45],"preference":[46],"feedback":[47],"from":[48],"an":[49],"LLM":[50],"judge.PDO":[51],"casts":[52],"selection":[54],"as":[55],"dueling-bandit":[57],"problem":[58],"and":[59,92],"combines":[60],"(i)":[61],"Double":[62],"Thompson":[63],"Sampling":[64],"prioritize":[66],"informative":[67],"comparisons":[68],"under":[69,110],"fixed":[71],"judge":[72],"budget,":[73],"with":[74],"(ii)":[75],"top-performer":[76],"guided":[77],"mutation":[78],"expand":[80],"candidate":[82],"pool":[83],"while":[84,105],"pruning":[85],"weak":[86],"prompts.Experiments":[87],"BIGbench":[89],"Hard":[90],"(BBH)":[91],"MS":[93],"MARCO":[94],"show":[95],"PDO":[97],"consistently":[98],"identifies":[99],"stronger":[100],"prompts":[101],"than":[102],"baselines,":[104],"offering":[106],"favorable":[107],"quality-cost":[108],"trade-offs":[109],"constrained":[111],"comparison":[112],"budgets.":[113]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}