{"id":"https://openalex.org/W4406612344","doi":"https://doi.org/10.1109/smc54092.2024.10831008","title":"Issue Title Generation: How Far Can Large Language Models Go?","display_name":"Issue Title Generation: How Far Can Large Language Models Go?","publication_year":2024,"publication_date":"2024-10-06","ids":{"openalex":"https://openalex.org/W4406612344","doi":"https://doi.org/10.1109/smc54092.2024.10831008"},"language":"en","primary_location":{"id":"doi:10.1109/smc54092.2024.10831008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5077711852","display_name":"Jun Yang","orcid":"https://orcid.org/0000-0003-0062-8124"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Yang","raw_affiliation_strings":["School of Computer Science, Beijing Information Science and Technology University,Beijing,China,100101"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing Information Science and Technology University,Beijing,China,100101","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008113307","display_name":"Shifan Liu","orcid":"https://orcid.org/0000-0003-0432-5358"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shifan Liu","raw_affiliation_strings":["School of Computer Science, Beijing Information Science and Technology University,Beijing,China,100101"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing Information Science and Technology University,Beijing,China,100101","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035451183","display_name":"Qifan He","orcid":null},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qifan He","raw_affiliation_strings":["School of Computer Science, Beijing Information Science and Technology University,Beijing,China,100101"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing Information Science and Technology University,Beijing,China,100101","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103665064","display_name":"Songcheng Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songcheng Xie","raw_affiliation_strings":["School of Computer Science, Beijing Information Science and Technology University,Beijing,China,100101"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing Information Science and Technology University,Beijing,China,100101","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071655887","display_name":"Zhanqi Cui","orcid":"https://orcid.org/0000-0002-5537-9236"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanqi Cui","raw_affiliation_strings":["School of Computer Science, Beijing Information Science and Technology University,Beijing,China,100101"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing Information Science and Technology University,Beijing,China,100101","institution_ids":["https://openalex.org/I78675632"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78675632"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2480","last_page":"2485"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8029000163078308,"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":0.8029000163078308,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.7914999723434448,"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":0.7265957593917847}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7265957593917847}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc54092.2024.10831008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2058591750","https://openalex.org/W2101105183","https://openalex.org/W2133286915","https://openalex.org/W2164577291","https://openalex.org/W3084484304","https://openalex.org/W3095319910","https://openalex.org/W4283371798","https://openalex.org/W4296143043","https://openalex.org/W4318069287","https://openalex.org/W4388483119","https://openalex.org/W4389544332","https://openalex.org/W4392903122","https://openalex.org/W6678262379","https://openalex.org/W6682631176","https://openalex.org/W6766356304","https://openalex.org/W7015831105"],"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/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"In":[0,176],"open-source":[1],"software":[2,10],"and":[3,142,192,199,225,232],"platforms,":[4],"developers":[5,37],"utilize":[6],"issues":[7],"to":[8,47,73,108,197,203],"record":[9],"failures":[11],"or":[12,50],"propose":[13,114],"new":[14],"features.":[15],"The":[16],"title":[17,96],"of":[18,88,105,127,136,167,185,205,229],"an":[19],"issue,":[20],"which":[21,138,219],"is":[22],"a":[23,33,54,86,115,182],"mandatory":[24],"field,":[25],"should":[26],"accurately":[27],"describe":[28],"the":[29,102,125,165,177,206,216],"core":[30],"content":[31],"in":[32,41,187,190,194,215,227],"concise":[34],"way.":[35],"However,":[36],"often":[38],"face":[39],"challenges":[40],"crafting":[42],"high-quality":[43],"issue":[44,64,95,168],"titles":[45,169],"due":[46],"insufficient":[48],"experience":[49],"limited":[51],"proficiency.":[52],"As":[53],"result,":[55],"researchers":[56],"have":[57,81],"proposed":[58],"several":[59],"methods":[60],"for":[61,94,150],"automatically":[62],"generating":[63],"titles,":[65],"but":[66],"typically":[67],"relying":[68],"on":[69],"constructing":[70],"large":[71],"datasets":[72],"train":[74],"models.":[75],"Recently,":[76],"Large":[77],"Language":[78],"Models":[79],"(LLMs)":[80],"exhibited":[82],"exceptional":[83],"performance":[84,201,214],"across":[85],"variety":[87],"general":[89],"tasks,":[90],"suggesting":[91],"significant":[92],"potential":[93],"generation.":[97],"Initial":[98],"experiments":[99],"indicate":[100],"that":[101,160,204],"direct":[103],"application":[104],"LLMs":[106,128,172],"fails":[107],"yield":[109],"satisfactory":[110],"results.":[111],"Therefore,":[112],"we":[113],"method":[116,208],"named":[117],"LBITG":[118,123,161,180,211],"(LLMs-Based":[119],"Issue":[120],"Title":[121],"Generation).":[122],"enhances":[124],"effectiveness":[126],"by":[129,171,222],"providing":[130],"contextual":[131],"information":[132],"through":[133],"four":[134],"types":[135],"prompts,":[137],"include":[139],"example":[140],"prompt":[141],"label":[143],"prompt.":[144],"These":[145],"prompts":[146],"serve":[147],"as":[148],"guidance":[149],"LLMs,":[151],"thereby":[152],"further":[153],"improving":[154],"their":[155],"performance.":[156],"Experimental":[157],"results":[158],"demonstrate":[159],"can":[162],"significantly":[163],"enhance":[164],"quality":[166],"generated":[170],"without":[173],"any":[174],"training.":[175],"within-project":[178],"scenario,":[179,218],"achieves":[181,200],"minimum":[183],"improvement":[184],"111.29%":[186],"ROUGE,":[188],"104.54%":[189],"BLEU,":[191],"188.48%":[193],"METEOR":[195],"compared":[196],"iTAPE,":[198],"comparable":[202],"SOTA":[207],"iTiger.":[209],"Moreover,":[210],"demonstrates":[212],"superior":[213],"cross-project":[217],"outperforms":[220],"iTiger":[221],"25.33%,":[223],"30.14%,":[224],"27.29%":[226],"terms":[228],"ROUGE-1,":[230],"BLEU-1,":[231],"METEOR,":[233],"respectively.":[234]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}