{"id":"https://openalex.org/W4417158997","doi":"https://doi.org/10.3390/info16121092","title":"Chain-of-Thought Prompt Optimization via Adversarial Learning","display_name":"Chain-of-Thought Prompt Optimization via Adversarial Learning","publication_year":2025,"publication_date":"2025-12-09","ids":{"openalex":"https://openalex.org/W4417158997","doi":"https://doi.org/10.3390/info16121092"},"language":"en","primary_location":{"id":"doi:10.3390/info16121092","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16121092","pdf_url":"https://www.mdpi.com/2078-2489/16/12/1092/pdf?version=1765282514","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/16/12/1092/pdf?version=1765282514","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Guang Yang","orcid":"https://orcid.org/0009-0005-0624-3913"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guang Yang","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan 430072, China"],"raw_orcid":"https://orcid.org/0009-0005-0624-3913","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003753939","display_name":"Xiantao Cai","orcid":"https://orcid.org/0000-0002-0764-5085"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiantao Cai","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan 430072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101908842","display_name":"Shaohe Wang","orcid":"https://orcid.org/0000-0003-1737-6912"},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]},{"id":"https://openalex.org/I74872605","display_name":"China Southern Power Grid (China)","ror":"https://ror.org/03hkh9419","country_code":"CN","type":"company","lineage":["https://openalex.org/I74872605"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohe Wang","raw_affiliation_strings":["Institute of Power Transmission and Transformation Technology, State Grid Zhejiang Electric Power Co., Ltd., Research Institute, Hangzhou 310014, China"],"raw_orcid":"https://orcid.org/0000-0003-1737-6912","affiliations":[{"raw_affiliation_string":"Institute of Power Transmission and Transformation Technology, State Grid Zhejiang Electric Power Co., Ltd., Research Institute, Hangzhou 310014, China","institution_ids":["https://openalex.org/I17442442","https://openalex.org/I74872605"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026501335","display_name":"Juhua Liu","orcid":"https://orcid.org/0000-0002-3907-8820"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juhua Liu","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan 430072, China"],"raw_orcid":"https://orcid.org/0000-0002-3907-8820","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5003753939"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19759963,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"12","first_page":"1092","last_page":"1092"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.39259999990463257,"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":0.39259999990463257,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.09260000288486481,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.07159999758005142,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/adversarial-system","display_name":"Adversarial system","score":0.8769000172615051},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5600000023841858},{"id":"https://openalex.org/keywords/commonsense-reasoning","display_name":"Commonsense reasoning","score":0.5515999794006348},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.3070000112056732},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.27320000529289246}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8769000172615051},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7303000092506409},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5702999830245972},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5600000023841858},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.5515999794006348},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5056999921798706},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info16121092","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16121092","pdf_url":"https://www.mdpi.com/2078-2489/16/12/1092/pdf?version=1765282514","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f1bb6c3cbbc74a978589e275c6eebecf","is_oa":true,"landing_page_url":"https://doaj.org/article/f1bb6c3cbbc74a978589e275c6eebecf","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 16, Iss 12, p 1092 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info16121092","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16121092","pdf_url":"https://www.mdpi.com/2078-2489/16/12/1092/pdf?version=1765282514","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417158997.pdf","grobid_xml":"https://content.openalex.org/works/W4417158997.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2251935656","https://openalex.org/W2593768305","https://openalex.org/W2890894339","https://openalex.org/W2962800603","https://openalex.org/W2963248348","https://openalex.org/W2963470893","https://openalex.org/W2964268978","https://openalex.org/W3004518555","https://openalex.org/W3034629641","https://openalex.org/W3103836116","https://openalex.org/W3159959439","https://openalex.org/W3170403598","https://openalex.org/W3210277894","https://openalex.org/W4309674289","https://openalex.org/W4327945465","https://openalex.org/W4389519405","https://openalex.org/W4389520756","https://openalex.org/W4389524159","https://openalex.org/W4402671583","https://openalex.org/W4402671743","https://openalex.org/W4402671783","https://openalex.org/W4402671980","https://openalex.org/W4404782964","https://openalex.org/W4408345571","https://openalex.org/W4411120093"],"related_works":[],"abstract_inverted_index":{"Chain-of-Thought":[0,38],"(CoT)":[1],"prompting":[2],"has":[3],"demonstrated":[4],"strong":[5],"effectiveness":[6,187],"in":[7],"improving":[8],"the":[9,124,174,182,192,198,213],"reasoning":[10,93,136,195,208],"capabilities":[11],"of":[12,100,176,188,207],"Large":[13],"Language":[14],"Models":[15],"(LLMs).":[16],"However,":[17],"existing":[18],"CoT":[19,74,180],"optimization":[20,229],"approaches":[21],"still":[22],"lack":[23],"systematic":[24],"mechanisms":[25],"for":[26,179],"evaluating":[27],"and":[28,58,62,70,76,88,104,134,138,144,197,216,225],"refining":[29],"prompts.":[30],"To":[31],"address":[32],"this":[33],"gap,":[34],"we":[35],"propose":[36],"Adversarial":[37],"(adv-CoT),":[39],"a":[40],"framework":[41,125],"that":[42,123,152],"introduces":[43],"adversarial":[44,177],"learning":[45],"into":[46,222],"prompt":[47,54,228],"optimization.":[48],"Adv-CoT":[49],"iteratively":[50],"refines":[51],"an":[52,97],"initial":[53],"through":[55],"generator\u2013discriminator":[56],"interactions":[57],"integrates":[59],"both":[60,109],"feedback":[61],"verification":[63],"mechanisms.":[64],"This":[65],"process":[66],"enables":[67],"more":[68,226],"targeted":[69],"interpretable":[71],"improvements":[72,153],"to":[73,203,218],"instructions":[75],"demonstrations.":[77],"We":[78,210],"evaluate":[79],"adv-CoT":[80,95,189],"on":[81,102,106,132,142,157,163,191],"twelve":[82],"datasets":[83],"across":[84],"commonsense,":[85],"factual,":[86],"symbolic,":[87],"arithmetic":[89],"reasoning.":[90],"Across":[91],"12":[92],"datasets,":[94],"yields":[96,126],"average":[98],"improvement":[99],"4.44%":[101],"GPT-3.5-turbo":[103],"1.08%":[105],"GPT-4o-mini,":[107],"with":[108],"gains":[110],"being":[111],"statistically":[112,155],"significant":[113],"(paired":[114],"t-test,":[115],"p":[116],"&lt;":[117],"0.05).":[118],"The":[119,186],"experimental":[120],"results":[121,162],"show":[122],"consistent":[127],"but":[128],"task-dependent":[129],"gains,":[130],"particularly":[131],"numerical":[133],"factual":[135],"tasks,":[137],"maintains":[139],"competitive":[140],"performance":[141],"symbolic":[143],"commonsense":[145],"benchmarks.":[146],"Paired":[147],"significance":[148],"tests":[149],"further":[150,220],"indicate":[151],"are":[154],"reliable":[156],"high-capacity":[158],"proprietary":[159],"models,":[160],"while":[161],"smaller":[164],"open-source":[165],"models":[166],"exhibit":[167],"greater":[168],"variance.":[169],"Although":[170],"these":[171],"findings":[172],"demonstrate":[173],"promise":[175],"refinement":[178],"prompting,":[181],"conclusions":[183],"remain":[184],"preliminary.":[185],"depends":[190],"base":[193],"model\u2019s":[194],"capability,":[196],"current":[199],"evaluation":[200],"is":[201],"limited":[202],"four":[204],"major":[205],"categories":[206],"tasks.":[209],"will":[211],"release":[212],"full":[214],"implementation":[215],"prompts":[217],"support":[219],"investigation":[221],"broader":[223],"applications":[224],"generalizable":[227],"strategies.":[230]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-12-09T00:00:00"}
