SubmissionNumber#=%=#20 FinalPaperTitle#=%=#Does Pragmatic Transfer Help Euphemism Detection? Evidence from Target-Span Marking ShortPaperTitle#=%=# NumberOfPages#=%=#14 CopyrightSigned#=%=#Whitney Poh JobTitle#==# Organization#==# Abstract#==#Euphemism detection is often motivated as a pragmatic task: deciding whether a potentially euphemistic term (PET) is used euphemistically depends on context, communicative goals, politeness, topic sensitivity, and sentiment. A natural prediction is that auxiliary supervision from pragmatically related tasks should improve euphemism detection when target supervision is limited. We test this prediction for PET-style classification using XLM-R and mBERT in a feature-based transfer setting: auxiliary-tuned encoders are frozen and probed for euphemism detection. We compare sentence-level pragmatic proxy tasks with expression-level nonliteral tasks and with target inputs that either mark or omit the PET span. The results do not support a simple pragmatic-transfer account. Auxiliary transfer is unreliable, often reducing XLM-R performance and helping mBERT only inconsistently. The largest observed gains come from direct euphemism fine-tuning when the target PET is explicitly marked. The practical implication is to preserve target-span information and report source--target compatibility in transfer experiments. Author{1}{Firstname}#=%=#Whitney Author{1}{Lastname}#=%=#Poh Author{1}{Username}#=%=#whitneyp Author{1}{Orcid}#=%=#https://orcid.org/0009-0005-4430-8466 Author{1}{Email}#=%=#pohw1@montclair.edu Author{1}{Affiliation}#=%=#Montclair State University Author{2}{Firstname}#=%=#Noriko Author{2}{Lastname}#=%=#Takahashi Author{2}{Username}#=%=#takahashi_n Author{2}{Orcid}#=%=# Author{2}{Email}#=%=#takahashin1@montclair.edu Author{2}{Affiliation}#=%=#Montclair State University Author{3}{Firstname}#=%=#Patrick Author{3}{Lastname}#=%=#Lee Author{3}{Username}#=%=#leep6 Author{3}{Orcid}#=%=# Author{3}{Email}#=%=#leep6@montclair.edu Author{3}{Affiliation}#=%=#Montclair State University Author{4}{Firstname}#=%=#Julia Author{4}{Lastname}#=%=#Sammartino Author{4}{Username}#=%=#sammartino Author{4}{Orcid}#=%=# Author{4}{Email}#=%=#sammartinoj1@montclair.edu Author{4}{Affiliation}#=%=#Montclair State University Author{5}{Firstname}#=%=#Libby Author{5}{Lastname}#=%=#Barak Author{5}{Username}#=%=#libbyb Author{5}{Orcid}#=%=# Author{5}{Email}#=%=#libby.berk@gmail.com Author{5}{Affiliation}#=%=#Montclair State University Author{6}{Firstname}#=%=#Jing Author{6}{Lastname}#=%=#Peng Author{6}{Username}#=%=#pengj Author{6}{Orcid}#=%=# Author{6}{Email}#=%=#pengj@montclair.edu Author{6}{Affiliation}#=%=#Montclair State University Author{7}{Firstname}#=%=#Anna Author{7}{Lastname}#=%=#Feldman Author{7}{Username}#=%=#feldmana Author{7}{Orcid}#=%=#https://orcid.org/0000-0003-4146-5990 Author{7}{Email}#=%=#feldmana@montclair.edu Author{7}{Affiliation}#=%=#Montclair State University ========== èéáğö