{"id":"https://openalex.org/W4412888527","doi":"https://doi.org/10.18653/v1/2025.findings-acl.324","title":"SEK: Self-Explained Keywords Empower Large Language Models for Code Generation","display_name":"SEK: Self-Explained Keywords Empower Large Language Models for Code Generation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888527","doi":"https://doi.org/10.18653/v1/2025.findings-acl.324"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.324","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.324","pdf_url":"https://aclanthology.org/2025.findings-acl.324.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":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.324.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114188119","display_name":"Lishui Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lishui Fan","raw_affiliation_strings":["The State Key Laboratory of Blockchain and Data Security Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Blockchain and Data Security Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057551045","display_name":"Mouxiang Chen","orcid":"https://orcid.org/0000-0002-8341-1467"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mouxiang Chen","raw_affiliation_strings":["The State Key Laboratory of Blockchain and Data Security Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Blockchain and Data Security Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102825823","display_name":"Zhongxin Liu","orcid":"https://orcid.org/0000-0002-1981-1626"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongxin Liu","raw_affiliation_strings":["The State Key Laboratory of Blockchain and Data Security Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Blockchain and Data Security Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":9.9049,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.9781817,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"6249","last_page":"6278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9851999878883362,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9851999878883362,"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/T10028","display_name":"Topic Modeling","score":0.9807000160217285,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.977400004863739,"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":0.7393103241920471},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.6003929376602173},{"id":"https://openalex.org/keywords/code-generation","display_name":"Code generation","score":0.5884374380111694},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.5441187620162964},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3933654725551605},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.0976540744304657}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7393103241920471},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.6003929376602173},{"id":"https://openalex.org/C133162039","wikidata":"https://www.wikidata.org/wiki/Q1061077","display_name":"Code generation","level":3,"score":0.5884374380111694},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.5441187620162964},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3933654725551605},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0976540744304657},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.324","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.324","pdf_url":"https://aclanthology.org/2025.findings-acl.324.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.324","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.324","pdf_url":"https://aclanthology.org/2025.findings-acl.324.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":[{"id":"https://openalex.org/G260358288","display_name":null,"funder_award_id":"62202420","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412888527.pdf","grobid_xml":"https://content.openalex.org/works/W4412888527.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/W2163672025","https://openalex.org/W2048831961","https://openalex.org/W1606349578","https://openalex.org/W4399567378"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"have":[4],"achieved":[5],"impressive":[6],"performance":[7],"in":[8,44,83,112],"code":[9,27,54,74,113,153],"generation.Despite":[10],"the":[11,30,33,45,80,84,88,123,132,140],"remarkable":[12],"success,":[13],"we":[14,59],"observed":[15],"that":[16,106,137],"LLMs":[17,47,111,141],"often":[18],"misunderstand":[19],"or":[20],"overlook":[21],"some":[22],"problem-specific":[23],"undertrained":[24,39],"keywords":[25,40,148],"during":[26],"generation,":[28,114],"compromising":[29],"accuracy":[31],"of":[32,125],"generated":[34],"code.After":[35],"explicitly":[36],"explaining":[37,79],"these":[38],"using":[41],"well-trained":[42],"terms":[43,82],"prompt,":[46],"are":[48],"more":[49],"likely":[50],"to":[51,129,142,149],"generate":[52],"correct":[53],"implementation.Inspired":[55],"by":[56,76],"this":[57],"observation,":[58],"propose":[60],"a":[61],"novel":[62],"technique":[63],"named":[64],"SEK":[65,107,121,138],"(Self-Explained":[66],"Keywords),":[67],"which":[68],"empowers":[69],"an":[70],"LLM":[71,89],"for":[72],"better":[73],"generation":[75],"extracting":[77],"and":[78,99,117],"key":[81],"problem":[85],"description":[86],"with":[87,101],"itself.Comprehensive":[90],"experiments":[91],"across":[92],"four":[93],"benchmarks,":[94],"i.e.,":[95],"HumanEval(+),":[96],"MBPP(+),":[97],"APPS":[98],"Big-CodeBench,":[100],"five":[102],"representative":[103],"LLMs,":[104],"show":[105],"can":[108],"significantly":[109],"improve":[110],"yielding":[115],"substantial":[116],"consistent":[118],"gains.For":[119],"instance,":[120],"improves":[122],"Pass@1":[124],"DeepSeek-Coder-V2-Instruct":[126],"from":[127,146],"85.4%":[128],"93.3%":[130],"on":[131],"Humaneval":[133],"benchmark.Further":[134],"analysis":[135],"confirms":[136],"enables":[139],"shift":[143],"their":[144,150],"attention":[145],"low-frequency":[147],"corresponding":[151],"explanations.Our":[152],"is":[154],"available":[155],"at":[156],"https://github.com/ZJU-CTAG/SEK.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}