{"id":"https://openalex.org/W7166701717","doi":"https://doi.org/10.48550/arxiv.2606.29709","title":"Bash-Commenter: Leveraging Syntax-Aware Preference Optimization to Reinforce Large Language Model for Bash Code Comment Generation","display_name":"Bash-Commenter: Leveraging Syntax-Aware Preference Optimization to Reinforce Large Language Model for Bash Code Comment Generation","publication_year":2026,"publication_date":"2026-06-29","ids":{"openalex":"https://openalex.org/W7166701717","doi":"https://doi.org/10.48550/arxiv.2606.29709"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.29709","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29709","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.29709","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139665875","display_name":"Lei Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139709937","display_name":"Jingyuan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jingyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139653011","display_name":"Xin Eric Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139708371","display_name":"Li Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047301622","display_name":"F Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Fengjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139665511","display_name":"Peng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139676972","display_name":"Jia Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Jia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5085158197","display_name":"J Y","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Jiajia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.7675999999046326,"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":0.7675999999046326,"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/T13629","display_name":"Text Readability and Simplification","score":0.06289999932050705,"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":0.0414000004529953,"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/scripting-language","display_name":"Scripting language","score":0.6908000111579895},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.6455000042915344},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5508000254631042},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.45660001039505005},{"id":"https://openalex.org/keywords/natural-language-generation","display_name":"Natural language generation","score":0.44920000433921814},{"id":"https://openalex.org/keywords/readability","display_name":"Readability","score":0.4480000138282776},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.44749999046325684},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.40630000829696655}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7940999865531921},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.6908000111579895},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.6455000042915344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.574400007724762},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5508000254631042},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.5037999749183655},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.45660001039505005},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4528999924659729},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.44920000433921814},{"id":"https://openalex.org/C2778143727","wikidata":"https://www.wikidata.org/wiki/Q1820650","display_name":"Readability","level":2,"score":0.4480000138282776},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.40630000829696655},{"id":"https://openalex.org/C114408938","wikidata":"https://www.wikidata.org/wiki/Q333373","display_name":"Abstract syntax","level":3,"score":0.38690000772476196},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.37959998846054077},{"id":"https://openalex.org/C58646249","wikidata":"https://www.wikidata.org/wiki/Q127380","display_name":"Abstract syntax tree","level":3,"score":0.374099999666214},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3215999901294708},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.3156999945640564},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25769999623298645},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.29709","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29709","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.29709","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.29709","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6706551313400269}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Bash":[0,21,48,86,99,112],"script":[1],"comprehension":[2],"is":[3],"challenging":[4],"due":[5],"to":[6,131],"Bash's":[7],"syntactic":[8],"freedom":[9],"and":[10,29,51,114,143,161,168,173,181,192],"complex":[11],"command":[12],"structures.":[13],"Despite":[14],"its":[15],"critical":[16],"role":[17],"in":[18,189],"system":[19],"administration,":[20],"scripts":[22,87,146],"often":[23],"lack":[24],"adequate":[25],"comments,":[26],"hindering":[27],"readability":[28],"maintainability.":[30],"Existing":[31],"automated":[32],"comment":[33,71,187],"generation":[34,72],"approaches":[35],"face":[36],"two":[37],"main":[38],"challenges:":[39],"(1)":[40],"limited":[41],"training":[42],"datasets":[43],"that":[44],"inadequately":[45],"represent":[46],"real-world":[47],"usage":[49],"patterns;":[50],"(2)":[52],"insufficient":[53],"understanding":[54],"of":[55,83,111,141],"Bash-specific":[56],"concepts":[57],"by":[58,102,127],"Large":[59],"Language":[60],"Models":[61],"(LLMs).":[62],"To":[63],"address":[64],"these,":[65],"we":[66,78,92,117],"propose":[67],"Bash-Commenter,":[68],"an":[69],"advanced":[70],"method":[73,152],"based":[74],"on":[75,97],"LLaMA-3.1-8B.":[76],"First,":[77],"construct":[79],"a":[80,132],"comprehensive":[81],"dataset":[82],"complex,":[84],"multi-line":[85,178],"with":[88],"high-quality":[89],"comments.":[90],"Second,":[91],"conduct":[93],"Continual":[94],"Pre-training":[95],"(CPT)":[96],"large-scale":[98],"data,":[100],"followed":[101],"Supervised":[103],"Fine-tuning":[104],"(SFT),":[105],"strengthening":[106],"the":[107],"model's":[108],"foundational":[109],"knowledge":[110],"syntax":[113],"semantics.":[115],"Finally,":[116],"introduce":[118],"Syntax-Aware":[119],"Preference":[120],"Optimization":[121],"(SAPO),":[122],"which":[123],"constructs":[124],"preference":[125],"pairs":[126,140],"applying":[128],"atomic":[129],"operations":[130],"script's":[133],"Abstract":[134],"Syntax":[135],"Tree":[136],"(AST),":[137],"creating":[138],"minimal":[139],"correct":[142],"subtly":[144],"incorrect":[145],"for":[147,164,176],"fine-grained":[148],"semantics":[149],"learning.":[150],"Our":[151],"outperforms":[153],"state-of-the-art":[154],"baselines,":[155],"achieving":[156],"33.40%":[157],"BLEU-4,":[158,170],"58.26%":[159],"METEOR,":[160,172],"57.03%":[162],"ROUGE-L":[163,175],"1,064":[165],"single-line":[166],"commands,":[167],"22.15%":[169],"43.89%":[171],"32.80%":[174],"1,046":[177],"scripts.":[179],"Human":[180],"LLM":[182],"evaluations":[183],"further":[184],"confirm":[185],"superior":[186],"quality":[188],"correctness,":[190],"completeness,":[191],"naturalness.":[193]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}
