{"id":"https://openalex.org/W4416251169","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229367","title":"A Fine-tuned Approach to Code Summarization Generation Based on Keyword Augmentation and Contrastive Learning","display_name":"A Fine-tuned Approach to Code Summarization Generation Based on Keyword Augmentation and Contrastive Learning","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251169","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229367"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5100332030","display_name":"Huan Wang","orcid":"https://orcid.org/0000-0003-0113-4425"},"institutions":[{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]},{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huan Wang","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042930315","display_name":"Shenggen Ju","orcid":"https://orcid.org/0000-0003-3730-0755"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenggen Ju","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038107623","display_name":"Yujie Wan","orcid":"https://orcid.org/0000-0003-3121-3386"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujie Wan","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034287644","display_name":"Rongmei Zhao","orcid":"https://orcid.org/0000-0002-7078-060X"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongmei Zhao","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007706452","display_name":"Jun Ren","orcid":"https://orcid.org/0000-0002-0275-0783"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junlin Ren","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100332030"],"corresponding_institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.47438844,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.31839999556541443,"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"}},"topics":[{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.31839999556541443,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.3025999963283539,"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":0.1527000069618225,"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/automatic-summarization","display_name":"Automatic summarization","score":0.8256000280380249},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.6661999821662903},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4625999927520752},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4129999876022339},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.39800000190734863},{"id":"https://openalex.org/keywords/code-generation","display_name":"Code generation","score":0.39730000495910645},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.39590001106262207}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8341000080108643},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8256000280380249},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.6661999821662903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.546999990940094},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5131999850273132},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4625999927520752},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.39800000190734863},{"id":"https://openalex.org/C133162039","wikidata":"https://www.wikidata.org/wiki/Q1061077","display_name":"Code generation","level":3,"score":0.39730000495910645},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.39590001106262207},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3212999999523163},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30000001192092896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28630000352859497},{"id":"https://openalex.org/C199519371","wikidata":"https://www.wikidata.org/wiki/Q942695","display_name":"Source lines of code","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C134714966","wikidata":"https://www.wikidata.org/wiki/Q6934448","display_name":"Multi-document summarization","level":3,"score":0.2736000120639801},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.25920000672340393},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2133333349","https://openalex.org/W2163745066","https://openalex.org/W2807964941","https://openalex.org/W2894732341","https://openalex.org/W2911270308","https://openalex.org/W2949297108","https://openalex.org/W3034689979","https://openalex.org/W3043200283","https://openalex.org/W3098605233","https://openalex.org/W3109716606","https://openalex.org/W3196992070","https://openalex.org/W4221166942","https://openalex.org/W4229664840","https://openalex.org/W4237602468","https://openalex.org/W4237993802","https://openalex.org/W4250325350","https://openalex.org/W4307823382","https://openalex.org/W4312235155","https://openalex.org/W4315695014","https://openalex.org/W4315881678","https://openalex.org/W4317515535","https://openalex.org/W4320157521","https://openalex.org/W4384347367","https://openalex.org/W4385245566","https://openalex.org/W4385573373","https://openalex.org/W4386566814","https://openalex.org/W4389519352","https://openalex.org/W4390872323","https://openalex.org/W4401044119"],"related_works":[],"abstract_inverted_index":{"Code":[0],"summarization":[1,102,160],"generation":[2,75,103],"aims":[3],"to":[4,52,69,86,131,142,163,201,212],"automatically":[5],"produce":[6],"summaries":[7],"from":[8,147],"source":[9],"code":[10,23,31,39,88,101,134,145,159,168],"based":[11,35],"on":[12,36,59,192],"its":[13],"analysis,":[14],"providing":[15],"information":[16,128],"such":[17,72],"as":[18,73],"the":[19,54,60,74,81,118,151,166,172,213,223,235],"design":[20],"goals":[21],"of":[22,56,62,76,84,177,219,225,229],"segments":[24],"and":[25,80,108,188,234],"relevant":[26],"parameters.":[27],"Recently,":[28],"fine-tuning":[29,98],"generalized":[30,194],"models,":[32],"which":[33],"are":[34],"pre-trained":[37,184],"large-scale":[38],"datasets,":[40],"has":[41],"garnered":[42],"considerable":[43],"attention.":[44],"Several":[45],"studies":[46],"have":[47],"proposed":[48],"data":[49,79,122,230],"augmentation":[50,107,123],"methods":[51],"mitigate":[53],"limitation":[55],"dataset":[57],"sizes":[58],"effectiveness":[61,176],"fine-tuned":[63],"models.":[64],"However,":[65],"these":[66,92,148],"approaches":[67],"continue":[68],"face":[70],"challenges,":[71],"low-quality":[77],"augmented":[78],"limited":[82],"ability":[83],"models":[85],"capture":[87,144],"representations.":[89],"To":[90],"address":[91],"issues,":[93],"we":[94],"propose":[95],"CATS,":[96,198],"a":[97,113,121,138,154,217],"method":[99,124,141],"for":[100,158],"that":[104,125,197],"incorporates":[105],"keyword":[106,127],"contrastive":[109,139,232],"learning.":[110],"CATS":[111,178,226],"employs":[112],"two-stage":[114,236],"training":[115,237],"strategy.":[116,238],"In":[117,150],"first":[119,173],"stage,":[120,153],"retains":[126],"is":[129,161,179],"designed":[130],"construct":[132],"similar":[133],"pairs,":[135],"followed":[136],"by":[137],"learning":[140],"effectively":[143],"representations":[146,169],"pairs.":[149],"second":[152],"generic":[155],"autoregressive":[156],"task":[157],"used":[162],"further":[164],"refine":[165],"high-quality":[167],"obtained":[170],"in":[171,227],"stage.":[174],"The":[175],"evaluated":[180],"using":[181],"three":[182,208],"different":[183],"models:":[185],"CodeBERT,":[186],"GraphCodeBERT,":[187],"UniXcoder.":[189],"Experimental":[190],"results":[191],"two":[193],"datasets":[195],"demonstrate":[196],"when":[199],"applied":[200],"UniXcoder,":[202],"significantly":[203],"improves":[204],"performance":[205],"across":[206],"all":[207],"evaluation":[209],"metrics":[210],"compared":[211],"baseline":[214],"methods.":[215],"Moreover,":[216],"series":[218],"ablation":[220],"experiments":[221],"validate":[222],"contributions":[224],"terms":[228],"augmentation,":[231],"learning,":[233]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-14T00:00:00"}