{"id":"https://openalex.org/W4412887771","doi":"https://doi.org/10.18653/v1/2025.findings-acl.1025","title":"PromptWizard: Optimizing Prompts via Task-Aware, Feedback-Driven Self-Evolution","display_name":"PromptWizard: Optimizing Prompts via Task-Aware, Feedback-Driven Self-Evolution","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412887771","doi":"https://doi.org/10.18653/v1/2025.findings-acl.1025"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.1025","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1025","pdf_url":"https://aclanthology.org/2025.findings-acl.1025.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 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.1025.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5098937289","display_name":"Eshaan Agarwal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Eshaan Agarwal","raw_affiliation_strings":["Microsoft Research India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research India","institution_ids":["https://openalex.org/I4210124949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058989698","display_name":"Raghav Magazine","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Raghav Magazine","raw_affiliation_strings":["Microsoft Research India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research India","institution_ids":["https://openalex.org/I4210124949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101278709","display_name":"Joykirat Singh","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Joykirat Singh","raw_affiliation_strings":["Microsoft Research India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research India","institution_ids":["https://openalex.org/I4210124949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098937290","display_name":"Vivek Dani","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vivek Dani","raw_affiliation_strings":["Microsoft Research India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research India","institution_ids":["https://openalex.org/I4210124949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024685185","display_name":"Tanuja Ganu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tanuja Ganu","raw_affiliation_strings":["Microsoft Research India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research India","institution_ids":["https://openalex.org/I4210124949"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089950211","display_name":"Akshay Nambi","orcid":"https://orcid.org/0000-0002-0921-4828"},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Akshay Nambi","raw_affiliation_strings":["Microsoft Research India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research India","institution_ids":["https://openalex.org/I4210124949"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210124949"],"apc_list":null,"apc_paid":null,"fwci":3.346,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.92242494,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"19974","last_page":"20003"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.8849999904632568,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.8849999904632568,"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":0.7486535310745239},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7168642282485962},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4714720547199249},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08320531249046326}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7486535310745239},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7168642282485962},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4714720547199249},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08320531249046326},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.1025","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1025","pdf_url":"https://aclanthology.org/2025.findings-acl.1025.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 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.1025","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1025","pdf_url":"https://aclanthology.org/2025.findings-acl.1025.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 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412887771.pdf","grobid_xml":"https://content.openalex.org/works/W4412887771.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/W3196817267","https://openalex.org/W1976600725"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"have":[4],"transformed":[5],"AI":[6],"across":[7,89],"diverse":[8],"domains,":[9],"with":[10,94],"prompting":[11],"being":[12],"central":[13],"to":[14,74],"their":[15],"success":[16],"in":[17,86,111],"guiding":[18],"model":[19],"outputs.However,":[20],"manual":[21],"prompt":[22,44,69,83,127],"engineering":[23],"is":[24],"both":[25,68],"labor-intensive":[26],"and":[27,54,64,71,100,116,123],"domain-specific,":[28],"necessitating":[29],"the":[30],"need":[31],"for":[32,42],"automated":[33,40],"solutions.We":[34],"introduce":[35],"PromptWizard,":[36],"a":[37,47,51,108],"novel,":[38],"fully":[39],"framework":[41],"discrete":[43],"optimization,":[45],"utilizing":[46],"selfevolving,":[48],"self-adapting":[49],"mechanism.Through":[50],"feedback-driven":[52],"critique":[53],"synthesis":[55],"process,":[56],"PromptWizard":[57],"achieves":[58],"an":[59],"effective":[60],"balance":[61],"between":[62],"exploration":[63],"exploitation,":[65],"iteratively":[66],"refining":[67],"instructions":[70],"incontext":[72],"examples":[73],"generate":[75],"human-readable,":[76],"task-specific":[77],"prompts.This":[78],"guided":[79],"approach":[80],"systematically":[81],"improves":[82],"quality,":[84],"resulting":[85],"superior":[87],"performance":[88],"45":[90],"tasks.PromptWizard":[91],"excels":[92],"even":[93],"limited":[95],"training":[96],"data,":[97],"smaller":[98],"LLMs,":[99],"various":[101],"LLM":[102],"architectures.Additionally,":[103],"our":[104],"cost":[105],"analysis":[106],"reveals":[107],"substantial":[109],"reduction":[110],"API":[112],"calls,":[113],"token":[114],"usage,":[115],"overall":[117],"cost,":[118],"demonstrating":[119],"PromptWizard's":[120],"efficiency,":[121],"scalability,":[122],"advantages":[124],"over":[125],"existing":[126],"optimization":[128],"strategies.":[129]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
