{"id":"https://openalex.org/W7154712251","doi":"https://doi.org/10.48550/arxiv.2604.14585","title":"Prompt Optimization Is a Coin Flip: Diagnosing When It Helps in Compound AI Systems","display_name":"Prompt Optimization Is a Coin Flip: Diagnosing When It Helps in Compound AI Systems","publication_year":2026,"publication_date":"2026-04-16","ids":{"openalex":"https://openalex.org/W7154712251","doi":"https://doi.org/10.48550/arxiv.2604.14585"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.14585","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14585","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.14585","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133894626","display_name":"Xing Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133838679","display_name":"Guanghui Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Guanghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063371086","display_name":"Yanwei Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Yanwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133868147","display_name":"Wei Qiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133331041","display_name":"Ziyuan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ziyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133881514","display_name":"Bing Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Bing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133917530","display_name":"Peiyang He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Peiyang","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":false,"cited_by_count":0,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.2711000144481659,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.2711000144481659,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.09939999878406525,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.06080000102519989,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4821000099182129},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.41749998927116394},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.3587000072002411},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.34200000762939453},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.31709998846054077},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.30809998512268066}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5925999879837036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5209000110626221},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4821000099182129},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4212000072002411},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.3587000072002411},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29109999537467957},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2888000011444092},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.28299999237060547},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.25920000672340393}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.14585","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14585","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.14585","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14585","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Prompt":[0],"optimization":[1,15,71,78,123,165,187],"in":[2,84],"compound":[3],"AI":[4],"systems":[5],"is":[6,40,188],"statistically":[7],"indistinguishable":[8],"from":[9,61],"a":[10,133,147,155,169,180,191],"coin":[11,192],"flip:":[12],"across":[13],"72":[14],"runs":[16],"on":[17,33,44],"Claude":[18],"Haiku":[19],"4.5":[20],"(6":[21],"methods":[22,49],"$\\times$":[23,26],"4":[24],"tasks":[25],"3":[27],"repeats),":[28],"49%":[29],"score":[30],"below":[31],"zero-shot;":[32],"Amazon":[34],"Nova":[35],"Lite,":[36],"the":[37,85,127,135,160],"failure":[38],"rate":[39],"even":[41],"higher.":[42],"Yet":[43],"one":[45],"task,":[46],"all":[47,118],"six":[48],"improve":[50],"over":[51],"zero-shot":[52],"by":[53],"up":[54],"to":[55],"$+6.8$":[56],"points.":[57],"What":[58],"distinguishes":[59],"success":[60],"failure?":[62],"We":[63,144,167],"investigate":[64],"with":[65],"18,000":[66],"grid":[67],"evaluations":[68],"and":[69,82,101,122,179],"144":[70],"runs,":[72],"testing":[73],"two":[74],"assumptions":[75],"behind":[76],"end-to-end":[77],"tools":[79],"like":[80],"TextGrad":[81],"DSPy,":[83],"order":[86],"they":[87],"must":[88],"be":[89],"answered:":[90],"(A)":[91],"agent":[92,177],"prompts":[93,104],"interact,":[94],"requiring":[95],"joint":[96,164],"rather":[97],"than":[98],"independent":[99],"optimization,":[100],"(B)":[102],"individual":[103],"are":[105,112],"worth":[106],"optimizing":[107],"at":[108],"all.":[109],"Interaction":[110],"effects":[111],"never":[113],"significant":[114],"($p":[115],"&gt;":[116],"0.52$,":[117],"$F":[119],"&lt;":[120],"1.0$),":[121],"helps":[124],"only":[125],"when":[126],"task":[128],"has":[129],"exploitable":[130],"output":[131,157],"structure:":[132],"format":[134],"model":[136],"can":[137],"produce":[138],"but":[139],"does":[140],"not":[141],"default":[142],"to.":[143],"further":[145],"give":[146],"mechanistic":[148],"account:":[149],"instruction-tuning":[150],"compresses":[151],"input":[152],"phrasing":[153],"into":[154,194],"narrow":[156],"distribution,":[158],"eliminating":[159],"very":[161],"phrasing-sensitivity":[162],"that":[163,184],"assumes.":[166],"provide":[168],"two-stage":[170],"diagnostic:":[171],"an":[172,195],"\\$80":[173],"ANOVA":[174],"pre-test":[175],"for":[176],"coupling,":[178],"10-minute":[181],"headroom":[182],"test":[183],"predicts":[185],"whether":[186],"worthwhile,":[189],"turning":[190],"flip":[193],"informed":[196],"decision.":[197]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-18T00:00:00"}
