{"id":"https://openalex.org/W4392823735","doi":"https://doi.org/10.1145/3638584.3638618","title":"Exploiting Paraphrasers and Inverse Paraphrasers: A Novel Approach to Enhance English Writing Fluency through Improved Style Transfer Training Data","display_name":"Exploiting Paraphrasers and Inverse Paraphrasers: A Novel Approach to Enhance English Writing Fluency through Improved Style Transfer Training Data","publication_year":2023,"publication_date":"2023-12-08","ids":{"openalex":"https://openalex.org/W4392823735","doi":"https://doi.org/10.1145/3638584.3638618"},"language":"en","primary_location":{"id":"doi:10.1145/3638584.3638618","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3638584.3638618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Computer Science and Artificial Intelligence","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/A5030627932","display_name":"Zhendong Du","orcid":"https://orcid.org/0009-0002-0346-0232"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Zhendong Du","raw_affiliation_strings":["Graduate School of Information, Production and Systems of Library and Information Science, Waseda University, Japan"],"raw_orcid":"https://orcid.org/0009-0002-0346-0232","affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems of Library and Information Science, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007690546","display_name":"Kenji Hashimoto","orcid":"https://orcid.org/0000-0003-2300-6766"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kenji Hashimoto","raw_affiliation_strings":["Graduate School of Information, Production and Systems of Library and Information Science, Waseda University, Japan"],"raw_orcid":"https://orcid.org/0000-0003-2300-6766","affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems of Library and Information Science, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5030627932"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.3408,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68569718,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"346","last_page":"352"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9983999729156494,"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":0.9968000054359436,"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/fluency","display_name":"Fluency","score":0.8133792877197266},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6663316488265991},{"id":"https://openalex.org/keywords/style","display_name":"Style (visual arts)","score":0.6466092467308044},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4519287943840027},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4481038451194763},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.428707480430603},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.42624953389167786},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.39027976989746094},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.24280685186386108},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.17239701747894287},{"id":"https://openalex.org/keywords/mathematics-education","display_name":"Mathematics education","score":0.09192818403244019},{"id":"https://openalex.org/keywords/art","display_name":"Art","score":0.07177266478538513},{"id":"https://openalex.org/keywords/literature","display_name":"Literature","score":0.06471672654151917}],"concepts":[{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.8133792877197266},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6663316488265991},{"id":"https://openalex.org/C2776445246","wikidata":"https://www.wikidata.org/wiki/Q1792644","display_name":"Style (visual arts)","level":2,"score":0.6466092467308044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4519287943840027},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4481038451194763},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.428707480430603},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.42624953389167786},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39027976989746094},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.24280685186386108},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.17239701747894287},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.09192818403244019},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.07177266478538513},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.06471672654151917},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3638584.3638618","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3638584.3638618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8100000023841858}],"awards":[],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1999187286","https://openalex.org/W2101105183","https://openalex.org/W2250699521","https://openalex.org/W2325585290","https://openalex.org/W2470324779","https://openalex.org/W2530291685","https://openalex.org/W2589277916","https://openalex.org/W2741494657","https://openalex.org/W2963026768","https://openalex.org/W2963881719","https://openalex.org/W2979826702","https://openalex.org/W2995804722","https://openalex.org/W3100727892","https://openalex.org/W4385571532","https://openalex.org/W4385571866"],"related_works":["https://openalex.org/W2365169615","https://openalex.org/W1970538215","https://openalex.org/W2400151637","https://openalex.org/W2975827637","https://openalex.org/W2354089692","https://openalex.org/W595497825","https://openalex.org/W4236323843","https://openalex.org/W2002616876","https://openalex.org/W3174418441","https://openalex.org/W2551249631"],"abstract_inverted_index":{"In":[0,39],"the":[1,8,22,28,34,51,67,127,138],"realm":[2],"of":[3,10,24,30,36,69,73,104,129,140],"enhancing":[4],"English":[5,60,86,141,155],"writing":[6,25,61,142],"fluency,":[7],"scarcity":[9],"high-quality":[11],"training":[12,75],"data":[13],"has":[14],"perennially":[15],"posed":[16],"a":[17,46,70,98,150],"significant":[18],"challenge.":[19],"Moreover,":[20],"elevating":[21],"fluency":[23,143],"while":[26],"ensuring":[27],"preservation":[29],"semantic":[31],"integrity":[32],"compounds":[33],"intricacies":[35],"this":[37,40,64,78],"task.":[38],"study,":[41],"we":[42,80],"introduce":[43],"and":[44,53,132,168],"implement":[45],"style":[47,88],"converter":[48,65],"rooted":[49],"in":[50,137,161],"Paraphraser":[52,55],"Inverse":[54],"methodologies,":[56],"aimed":[57],"at":[58],"ameliorating":[59],"fluency.":[62],"Concurrently,":[63],"facilitated":[66],"generation":[68],"voluminous":[71],"corpus":[72],"synthetic":[74],"data.":[76],"Utilizing":[77],"data,":[79],"fine-tuned":[81],"GPT-2":[82],"to":[83],"forge":[84],"an":[85],"text":[87],"transfer":[89],"model.":[90],"Remarkably,":[91],"despite":[92],"our":[93,130],"model":[94],"being":[95],"trained":[96],"on":[97,120],"dataset":[99],"substantially":[100],"smaller":[101],"than":[102],"that":[103],"prevailing":[105],"baseline":[106],"methods,":[107],"it":[108],"exhibited":[109],"exemplary":[110],"performance":[111],"across":[112],"multiple":[113],"evaluation":[114],"metrics,":[115],"even":[116],"surpassing":[117],"these":[118],"baselines":[119],"certain":[121],"pivotal":[122],"indices.":[123],"These":[124],"findings":[125],"corroborate":[126],"efficacy":[128],"approach":[131],"underscore":[133],"its":[134],"immense":[135],"potential":[136],"domain":[139],"enhancement.":[144],"This":[145],"investigation":[146],"not":[147],"only":[148],"offers":[149],"novel":[151],"optimization":[152],"strategy":[153],"for":[154],"composition":[156],"but":[157],"also":[158],"furnishes":[159],"researchers":[160],"cognate":[162],"fields":[163],"with":[164],"fresh":[165],"research":[166],"perspectives":[167],"methodologies.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
