{"id":"https://openalex.org/W4296422545","doi":"https://doi.org/10.1145/3544902.3546251","title":"MMF3: Neural Code Summarization Based on Multi-Modal Fine-Grained Feature Fusion","display_name":"MMF3: Neural Code Summarization Based on Multi-Modal Fine-Grained Feature Fusion","publication_year":2022,"publication_date":"2022-09-07","ids":{"openalex":"https://openalex.org/W4296422545","doi":"https://doi.org/10.1145/3544902.3546251"},"language":"en","primary_location":{"id":"doi:10.1145/3544902.3546251","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3544902.3546251","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th 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/A5100656551","display_name":"Zheng Ma","orcid":"https://orcid.org/0000-0002-1867-894X"},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zheng Ma","raw_affiliation_strings":["Shandong Normal University, China"],"affiliations":[{"raw_affiliation_string":"Shandong Normal University, China","institution_ids":["https://openalex.org/I28006308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067001807","display_name":"Yuexiu Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuexiu Gao","raw_affiliation_strings":["Shandong Normal University, China"],"affiliations":[{"raw_affiliation_string":"Shandong Normal University, China","institution_ids":["https://openalex.org/I28006308"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lei Lyu","orcid":null},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Lyu","raw_affiliation_strings":["Shandong Normal University, China"],"affiliations":[{"raw_affiliation_string":"Shandong Normal University, China","institution_ids":["https://openalex.org/I28006308"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045065594","display_name":"Chen Lyu","orcid":"https://orcid.org/0000-0002-5044-1459"},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Lyu","raw_affiliation_strings":["Shandong Normal University, China"],"affiliations":[{"raw_affiliation_string":"Shandong Normal University, China","institution_ids":["https://openalex.org/I28006308"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100656551"],"corresponding_institution_ids":["https://openalex.org/I28006308"],"apc_list":null,"apc_paid":null,"fwci":1.3879,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.84372463,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"171","last_page":"182"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.9994999766349792,"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/T10260","display_name":"Software Engineering Research","score":0.998199999332428,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9945999979972839,"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":0.8802652359008789},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.8547852635383606},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.5225396156311035},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5182899832725525},{"id":"https://openalex.org/keywords/abstract-syntax-tree","display_name":"Abstract syntax tree","score":0.5139226913452148},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5109559893608093},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.48506394028663635},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.2990448474884033},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.2377694547176361},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.1004137396812439}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8802652359008789},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8547852635383606},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.5225396156311035},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5182899832725525},{"id":"https://openalex.org/C58646249","wikidata":"https://www.wikidata.org/wiki/Q127380","display_name":"Abstract syntax tree","level":3,"score":0.5139226913452148},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5109559893608093},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.48506394028663635},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.2990448474884033},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.2377694547176361},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.1004137396812439},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3544902.3546251","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3544902.3546251","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3548755090","display_name":null,"funder_award_id":"61602286, 61976127","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1593271688","https://openalex.org/W1956340063","https://openalex.org/W1970407057","https://openalex.org/W1989184611","https://openalex.org/W2001033929","https://openalex.org/W2018844270","https://openalex.org/W2034209539","https://openalex.org/W2039603939","https://openalex.org/W2081749632","https://openalex.org/W2082160726","https://openalex.org/W2107878631","https://openalex.org/W2133333349","https://openalex.org/W2148357053","https://openalex.org/W2164886519","https://openalex.org/W2166879716","https://openalex.org/W2294980783","https://openalex.org/W2516621648","https://openalex.org/W2574795845","https://openalex.org/W2600463316","https://openalex.org/W2741561716","https://openalex.org/W2884276923","https://openalex.org/W2888557792","https://openalex.org/W2949297108","https://openalex.org/W2964194820","https://openalex.org/W2979271470","https://openalex.org/W2997945091","https://openalex.org/W3011632945","https://openalex.org/W3034689979","https://openalex.org/W3086449553","https://openalex.org/W3091730360","https://openalex.org/W3175000455","https://openalex.org/W3176776234","https://openalex.org/W3179515446","https://openalex.org/W3182190622","https://openalex.org/W4206238733","https://openalex.org/W4249122235"],"related_works":["https://openalex.org/W2001919569","https://openalex.org/W4310447811","https://openalex.org/W4389751695","https://openalex.org/W3081644756","https://openalex.org/W2165004968","https://openalex.org/W2320787857","https://openalex.org/W3086207785","https://openalex.org/W3012064729","https://openalex.org/W2969229669","https://openalex.org/W2955426500"],"abstract_inverted_index":{"Background:":[0],"Code":[1],"summarization":[2,31,111],"automatically":[3],"generates":[4],"the":[5,12,17,73,77,89,104,147,168,189,218,224,230,243,252,275,278],"corresponding":[6],"natural":[7],"language":[8],"descriptions":[9],"according":[10],"to":[11,15,29,42,87,102,178,192,273],"input":[13],"code":[14,25,30,93,110,125,142,165,193,280],"characterize":[16],"function":[18],"implemented":[19],"by":[20,112],"source":[21,124],"code.":[22],"Comprehensiveness":[23],"of":[24,51,54,123,163,220,245,277],"representation":[26],"is":[27],"critical":[28],"task.":[32],"However,":[33],"most":[34],"existing":[35],"approaches":[36],"typically":[37],"use":[38,175],"coarse-grained":[39],"fusion":[40,157,162,238,263],"methods":[41],"integrate":[43],"multi-modal":[44],"features.":[45],"They":[46],"generally":[47],"represent":[48],"different":[49],"modalities":[50,96,166,186],"a":[52,64,81,133,154,266],"piece":[53],"code,":[55],"such":[56],"as":[57,67],"an":[58],"Abstract":[59],"Syntax":[60],"Tree":[61],"(AST)":[62],"and":[63,70,115,119,170,184,187,202,206,228,257],"token":[65,169,183],"sequence,":[66],"two":[68,74],"embeddings":[69],"then":[71],"fuse":[72,179],"ones":[75],"at":[76,126,167],"AST/code":[78],"levels.":[79,128,172],"Such":[80],"coarse":[82],"integration":[83],"makes":[84],"it":[85],"difficult":[86],"learn":[88],"correlations":[90],"between":[91,254],"fine-grained":[92,156,161,237,260],"elements":[94,256],"across":[95],"effectively.":[97],"Aims:":[98],"This":[99,130],"study":[100],"intends":[101],"improve":[103,242,274],"model\u2019s":[105],"prediction":[106],"performance":[107,219],"for":[108,140],"high-quality":[109],"accurately":[113],"aligning":[114],"fully":[116],"fusing":[117],"semantic":[118],"syntactic":[120],"structure":[121],"information":[122,180],"node/token":[127],"Method:":[129],"paper":[131],"proposes":[132],"Multi-Modal":[134],"Fine-grained":[135],"Feature":[136],"Fusion":[137],"approach":[138],"(MMF3)":[139],"neural":[141],"summarization.":[143,194],"The":[144,213],"method":[145,177,239],"uses":[146],"Transformer":[148],"architecture.":[149],"In":[150],"particular,":[151],"we":[152,174],"introduce":[153],"novel":[155],"method,":[158],"which":[159],"allows":[160],"multiple":[164],"node":[171],"Specifically,":[173],"this":[176],"from":[181],"both":[182],"AST":[185],"apply":[188],"fused":[190],"features":[191],"Results:":[195],"We":[196],"conduct":[197],"experiments":[198,232],"on":[199],"one":[200,203],"Java":[201],"Python":[204],"datasets,":[205],"evaluate":[207],"generated":[208,246,279],"summaries":[209],"using":[210],"four":[211],"metrics.":[212],"results":[214],"show":[215,233],"that:":[216],"1)":[217],"our":[221,235],"model":[222],"outperforms":[223],"current":[225],"state-of-the-art":[226],"models,":[227],"2)":[229],"ablation":[231],"that":[234],"proposed":[236],"can":[240,250,270],"effectively":[241],"accuracy":[244,276],"summaries.":[247,281],"Conclusion:":[248],"MMF3":[249],"mine":[251],"relationships":[253],"cross-modal":[255],"perform":[258],"accurate":[259],"element-level":[261],"alignment":[262],"accordingly.":[264],"As":[265],"result,":[267],"more":[268],"clues":[269],"be":[271],"provided":[272]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}