{"id":"https://openalex.org/W4403413145","doi":"https://doi.org/10.1145/3674805.3690751","title":"PromptLink: Multi-template prompt learning with adversarial training for issue-commit link recovery","display_name":"PromptLink: Multi-template prompt learning with adversarial training for issue-commit link recovery","publication_year":2024,"publication_date":"2024-10-15","ids":{"openalex":"https://openalex.org/W4403413145","doi":"https://doi.org/10.1145/3674805.3690751"},"language":"en","primary_location":{"id":"doi:10.1145/3674805.3690751","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3674805.3690751","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049366790","display_name":"Yang Deng","orcid":"https://orcid.org/0000-0002-2795-6796"},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Deng","raw_affiliation_strings":["School of Computer Science and Artificial Intelligence, Wuhan Textile University, China"],"raw_orcid":"https://orcid.org/0000-0002-2795-6796","affiliations":[{"raw_affiliation_string":"School of Computer Science and Artificial Intelligence, Wuhan Textile University, China","institution_ids":["https://openalex.org/I4210119942"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024168142","display_name":"Bangchao Wang","orcid":"https://orcid.org/0000-0001-6920-1810"},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bangchao Wang","raw_affiliation_strings":["School of Computer Science and Artificial Intelligence, Wuhan Textile University, China"],"raw_orcid":"https://orcid.org/0000-0001-6920-1810","affiliations":[{"raw_affiliation_string":"School of Computer Science and Artificial Intelligence, Wuhan Textile University, China","institution_ids":["https://openalex.org/I4210119942"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhiyuan Zou","orcid":"https://orcid.org/0009-0006-2256-479X"},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Zou","raw_affiliation_strings":["Engineering Research Center of Hubei Province for Clothing Information, Wuhan Textile University, China"],"raw_orcid":"https://orcid.org/0009-0006-2256-479X","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Hubei Province for Clothing Information, Wuhan Textile University, China","institution_ids":["https://openalex.org/I4210119942"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101862257","display_name":"Luyao Ye","orcid":"https://orcid.org/0000-0001-9347-9994"},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luyao Ye","raw_affiliation_strings":["Engineering Research Center of Hubei Province for Clothing Information, Wuhan Textile University, China"],"raw_orcid":"https://orcid.org/0000-0001-9347-9994","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Hubei Province for Clothing Information, Wuhan Textile University, China","institution_ids":["https://openalex.org/I4210119942"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210119942"],"apc_list":null,"apc_paid":null,"fwci":0.5972,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74229592,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"461","last_page":"467"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.998199999332428,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.998199999332428,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12127","display_name":"Software System Performance and Reliability","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/commit","display_name":"Commit","score":0.8738789558410645},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8161628246307373},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7415685653686523},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6486732959747314},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.580623984336853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44550928473472595},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3529428243637085},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.18082979321479797},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08736449480056763}],"concepts":[{"id":"https://openalex.org/C153180980","wikidata":"https://www.wikidata.org/wiki/Q19776675","display_name":"Commit","level":2,"score":0.8738789558410645},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8161628246307373},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7415685653686523},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6486732959747314},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.580623984336853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44550928473472595},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3529428243637085},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.18082979321479797},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08736449480056763},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3674805.3690751","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3674805.3690751","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1985871111","https://openalex.org/W1988019447","https://openalex.org/W2110498832","https://openalex.org/W2122702470","https://openalex.org/W2130463457","https://openalex.org/W2560775194","https://openalex.org/W2618735982","https://openalex.org/W2767394365","https://openalex.org/W2891045772","https://openalex.org/W2921638471","https://openalex.org/W2972155226","https://openalex.org/W3081648799","https://openalex.org/W3098598077","https://openalex.org/W3162044134","https://openalex.org/W3180181113","https://openalex.org/W3185341429","https://openalex.org/W3194836374","https://openalex.org/W3215177922","https://openalex.org/W4254692035","https://openalex.org/W4312310776","https://openalex.org/W4365211555","https://openalex.org/W4372348710","https://openalex.org/W4384039146","https://openalex.org/W4386076590"],"related_works":["https://openalex.org/W4367365664","https://openalex.org/W4385326140","https://openalex.org/W4293227618","https://openalex.org/W2136634148","https://openalex.org/W3122851392","https://openalex.org/W3122800671","https://openalex.org/W4250708772","https://openalex.org/W4288862737","https://openalex.org/W1984769753","https://openalex.org/W2502115930"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"Prompt":[3],"Learning,":[4],"based":[5],"on":[6,131,174],"pre-training,":[7],"prompting,":[8],"and":[9,39,51,119,135,165,183,190],"prediction,":[10],"has":[11],"achieved":[12],"significant":[13],"success":[14],"in":[15,61],"natural":[16],"language":[17,36],"processing":[18],"(NLP).":[19],"The":[20,142,195],"current":[21],"issue-commit":[22,88],"link":[23,89],"recovery":[24,90],"(ILR)":[25],"method":[26,83],"converts":[27],"the":[28,48,58,65,70,74,94,102,112,125],"ILR":[29,49,95],"into":[30,97],"a":[31,79,98,105],"classification":[32],"task":[33,50,96,100],"using":[34],"pre-trained":[35],"models":[37],"(PLMs)":[38],"dedicated":[40],"neural":[41],"networks.":[42],"However,":[43],"due":[44],"to":[45,77,110,123],"inconsistencies":[46],"between":[47],"PLMs,":[52],"these":[53],"methods":[54,173,191],"not":[55,179],"fully":[56],"leverage":[57],"semantic":[59],"information":[60],"PLMs.":[62],"To":[63],"imitate":[64],"above":[66],"problem,":[67],"we":[68],"make":[69],"first":[71],"trial":[72],"of":[73,151,154,157,160,163,167,198],"new":[75,188],"paradigm":[76],"propose":[78],"Multi-template":[80,106],"prompt":[81],"learning":[82],"with":[84],"adversarial":[85,121],"training":[86,122],"for":[87,192],"(PromptLink),":[91],"which":[92],"transforms":[93],"cloze":[99],"through":[101],"template.":[103],"Specifically,":[104],"PromptLink":[107,146,178,199],"is":[108,200],"designed":[109],"enhance":[111],"generalisation":[113,184],"capability":[114],"by":[115],"integrating":[116],"various":[117],"templates":[118],"adopting":[120],"mitigate":[124],"model":[126],"overfitting.":[127],"Experiments":[128],"are":[129],"conducted":[130],"six":[132,139],"open-source":[133],"projects":[134],"comprehensively":[136],"evaluated":[137],"across":[138],"commonly":[140],"measures.":[141,176],"results":[143],"show":[144],"that":[145],"achieves":[147],"an":[148],"average":[149],"F1":[150],"96.10%,":[152],"Precision":[153],"96.49%,":[155],"Recall":[156],"95.92%,":[158],"MCC":[159],"94.04%,":[161],"AUC":[162],"96.05%,":[164],"ACC":[166],"98.15%,":[168],"significantly":[169],"outperforming":[170],"existing":[171],"state-of-the-art":[172],"all":[175],"Overall,":[177],"only":[180],"enhances":[181],"performance":[182],"but":[185],"also":[186],"emerges":[187],"ideas":[189],"future":[193],"research.":[194],"source":[196],"code":[197],"available":[201],"at":[202],"https://figshare.com/s/6130d42ff464c579cdec.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
