{"id":"https://openalex.org/W7162766107","doi":"https://doi.org/10.48550/arxiv.2605.29365","title":"Casual as an Anchor: Resolving Supervision Misalignment in Formality Transfer Dataset","display_name":"Casual as an Anchor: Resolving Supervision Misalignment in Formality Transfer Dataset","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7162766107","doi":"https://doi.org/10.48550/arxiv.2605.29365"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.29365","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29365","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"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.2605.29365","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137391560","display_name":"Hyojeong Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Hyojeong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036169669","display_name":"Hyukhun Koh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koh, Hyukhun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137317610","display_name":"Minsung Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Minsung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137374371","display_name":"Kyomin Jung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jung, Kyomin","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":0.2953999936580658,"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":0.2953999936580658,"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":0.19290000200271606,"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":0.1265999972820282,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/formality","display_name":"Formality","score":0.9545000195503235},{"id":"https://openalex.org/keywords/casual","display_name":"Casual","score":0.7206000089645386},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7027999758720398},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5077999830245972},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5030999779701233},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.47119998931884766},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4259999990463257},{"id":"https://openalex.org/keywords/framing","display_name":"Framing (construction)","score":0.4235000014305115},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.3702000081539154}],"concepts":[{"id":"https://openalex.org/C2777159308","wikidata":"https://www.wikidata.org/wiki/Q1757948","display_name":"Formality","level":2,"score":0.9545000195503235},{"id":"https://openalex.org/C2781426162","wikidata":"https://www.wikidata.org/wiki/Q2275793","display_name":"Casual","level":2,"score":0.7206000089645386},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7027999758720398},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6876999735832214},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5077999830245972},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5030999779701233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5019999742507935},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.47119998931884766},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4259999990463257},{"id":"https://openalex.org/C169087156","wikidata":"https://www.wikidata.org/wiki/Q2131593","display_name":"Framing (construction)","level":2,"score":0.4235000014305115},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4180000126361847},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41760000586509705},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.3702000081539154},{"id":"https://openalex.org/C2780876879","wikidata":"https://www.wikidata.org/wiki/Q3054749","display_name":"Meaning (existential)","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33180001378059387},{"id":"https://openalex.org/C75606506","wikidata":"https://www.wikidata.org/wiki/Q1049183","display_name":"Formal methods","level":2,"score":0.3285999894142151},{"id":"https://openalex.org/C2985583900","wikidata":"https://www.wikidata.org/wiki/Q722617","display_name":"Formal description","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.31150001287460327},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2533000111579895},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.25040000677108765},{"id":"https://openalex.org/C146499914","wikidata":"https://www.wikidata.org/wiki/Q5469969","display_name":"Formal semantics (linguistics)","level":2,"score":0.2502000033855438},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.29365","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29365","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.29365","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.29365","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Formality":[0],"transfer":[1,97],"is":[2],"commonly":[3],"framed":[4],"as":[5,29,98,119],"a":[6,21,73,99,104,109,135],"symmetric":[7],"bidirectional":[8],"task":[9],"between":[10],"informal":[11],"and":[12,114,151,190,197,210],"formal":[13,61,70],"registers.":[14],"We":[15,63,107,177],"argue":[16],"that":[17,52,81,124,180],"this":[18,65,92,130],"framing":[19],"conceals":[20],"supervision":[22,126,139,205],"design":[23,206],"flaw":[24],"in":[25,166,218],"existing":[26],"benchmarks":[27],"such":[28],"GYAFC:":[30],"binary":[31,105],"human":[32,41,155],"rewrites":[33],"encode":[34],"relative":[35],"stylistic":[36,208],"shifts":[37],"rather":[38,102],"than":[39,103,175],"absolute":[40],"notions":[42],"of":[43,76,194,214],"formality.":[44],"Consequently,":[45],"models":[46],"learn":[47],"to":[48,58,83,163],"generate":[49],"pseudo-formal":[50],"outputs":[51],"satisfy":[53],"benchmark":[54,69,216],"labels":[55,71],"while":[56],"failing":[57],"produce":[59],"genuinely":[60],"language.":[62],"quantify":[64],"misalignment":[66],"by":[67],"re-evaluating":[68],"under":[72],"human-aligned":[74],"definition":[75],"formality,":[77],"revealing":[78],"substantial":[79],"discrepancies":[80],"propagate":[82],"consistent":[84],"informal-to-formal":[85,149,168],"failures":[86,150],"across":[87,140],"model":[88],"families.":[89],"To":[90],"address":[91],"issue,":[93],"we":[94,132],"reconceptualize":[95],"formality":[96],"graded":[100],"dimension":[101],"attribute.":[106],"introduce":[108,133],"three-level":[110],"spectrum:":[111],"informal,":[112],"casual,":[113],"formal,":[115],"where":[116],"casual":[117],"serves":[118],"an":[120],"explicit":[121],"intermediate":[122],"state":[123],"clarifies":[125],"signals.":[127],"Based":[128],"on":[129,145],"framework,":[131],"3LF,":[134],"dataset":[136],"providing":[137],"parallel":[138],"all":[141],"three":[142],"levels.":[143],"Training":[144],"3LF":[146,171],"substantially":[147],"reduces":[148],"improves":[152,160],"alignment":[153,209],"with":[154],"perception.":[156],"For":[157],"example,":[158],"GPT-4.1-nano":[159],"from":[161],"0.06":[162],"0.88":[164],"F1":[165],"the":[167,212],"direction":[169],"despite":[170],"being":[172],"significantly":[173],"smaller":[174],"GYAFC.":[176],"further":[178],"demonstrate":[179,203],"these":[181],"gains":[182],"cannot":[183],"be":[184],"reproduced":[185],"through":[186],"in-context":[187],"learning":[188],"alone":[189],"provide":[191],"qualitative":[192],"analyses":[193],"ambiguity-driven":[195],"errors":[196],"meaning":[198],"distortions.":[199],"Overall,":[200],"our":[201],"findings":[202],"how":[204],"shapes":[207],"highlight":[211],"importance":[213],"alignment-aware":[215],"construction":[217],"controllable":[219],"text":[220],"generation.":[221]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-30T00:00:00"}
