{"id":"https://openalex.org/W4375869925","doi":"https://doi.org/10.48550/arxiv.2305.03495","title":"Automatic Prompt Optimization with \"Gradient Descent\" and Beam Search","display_name":"Automatic Prompt Optimization with \"Gradient Descent\" and Beam Search","publication_year":2023,"publication_date":"2023-05-04","ids":{"openalex":"https://openalex.org/W4375869925","doi":"https://doi.org/10.48550/arxiv.2305.03495"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2305.03495","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.03495","pdf_url":"https://arxiv.org/pdf/2305.03495","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2305.03495","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065744065","display_name":"Reid Pryzant","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Pryzant, Reid","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037853792","display_name":"Dan Iter","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Iter, Dan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101439736","display_name":"Jerry Li","orcid":"https://orcid.org/0000-0002-8774-826X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jerry","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001487198","display_name":"Yin Tat Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Yin Tat","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100355246","display_name":"Chenguang Zhu","orcid":"https://orcid.org/0000-0002-3549-0826"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Chenguang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5089195158","display_name":"Michael Zeng","orcid":"https://orcid.org/0000-0001-5302-5883"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Michael","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5065744065"],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9929999709129333,"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"}},{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/gradient-descent","display_name":"Gradient descent","score":0.7842917442321777},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7831555604934692},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7719796895980835},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.573136031627655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5264045596122742},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5052734017372131},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4945988357067108},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.482927531003952},{"id":"https://openalex.org/keywords/descent","display_name":"Descent (aeronautics)","score":0.44642001390457153},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.414715975522995}],"concepts":[{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.7842917442321777},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7831555604934692},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7719796895980835},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.573136031627655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5264045596122742},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5052734017372131},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4945988357067108},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.482927531003952},{"id":"https://openalex.org/C2776637919","wikidata":"https://www.wikidata.org/wiki/Q624380","display_name":"Descent (aeronautics)","level":2,"score":0.44642001390457153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.414715975522995},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2305.03495","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.03495","pdf_url":"https://arxiv.org/pdf/2305.03495","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2305.03495","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2305.03495","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2305.03495","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.03495","pdf_url":"https://arxiv.org/pdf/2305.03495","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4375869925.pdf","grobid_xml":"https://content.openalex.org/works/W4375869925.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4206903459","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W4231621013","https://openalex.org/W4362706668","https://openalex.org/W2015288657","https://openalex.org/W3008318776","https://openalex.org/W2041416246","https://openalex.org/W3020853991"],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"have":[4],"shown":[5],"impressive":[6],"performance":[7,148],"as":[8],"general":[9],"purpose":[10],"agents,":[11],"but":[12],"their":[13],"abilities":[14],"remain":[15],"highly":[16],"dependent":[17],"on":[18],"prompts":[19],"which":[20,42,112],"are":[21,80,102],"hand":[22],"written":[23],"with":[24],"onerous":[25],"trial-and-error":[26],"effort.":[27],"We":[28],"propose":[29],"a":[30,105],"simple":[31],"and":[32,58,108,124,143],"nonparametric":[33],"solution":[34],"to":[35,49,55,68,151,156],"this":[36],"problem,":[37],"Automatic":[38,134],"Prompt":[39,135],"Optimization":[40,136],"(APO),":[41],"is":[43],"inspired":[44],"by":[45,86,104,149,153],"numerical":[46],"gradient":[47,99],"descent":[48,100],"automatically":[50],"improve":[51,144],"prompts,":[52],"assuming":[53],"access":[54],"training":[56],"data":[57,67,155],"an":[59,145],"LLM":[60,129],"API.":[61],"The":[62,78],"algorithm":[63],"uses":[64],"minibatches":[65],"of":[66,95,128],"form":[69],"natural":[70],"language":[71],"\"gradients\"":[72],"that":[73,133],"criticize":[74],"the":[75,84,88,91,96,125],"current":[76],"prompt.":[77],"gradients":[79],"then":[81],"\"propagated\"":[82],"into":[83,161],"prompt":[85,89,140],"editing":[87,141],"in":[90],"opposite":[92],"semantic":[93],"direction":[94],"gradient.":[97],"These":[98],"steps":[101],"guided":[103],"beam":[106],"search":[107],"bandit":[109],"selection":[110],"procedure":[111],"significantly":[113],"improves":[114],"algorithmic":[115],"efficiency.":[116],"Preliminary":[117],"results":[118],"across":[119],"three":[120],"benchmark":[121],"NLP":[122],"tasks":[123],"novel":[126],"problem":[127],"jailbreak":[130],"detection":[131],"suggest":[132],"can":[137],"outperform":[138],"prior":[139],"techniques":[142],"initial":[146],"prompt's":[147],"up":[150],"31%,":[152],"using":[154],"rewrite":[157],"vague":[158],"task":[159],"descriptions":[160],"more":[162],"precise":[163],"annotation":[164],"instructions.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
