Fair decisions, clear reasons: Creating Fuzzy AI with fairness built in from the start - Asia Research News |
<a href="https://news.google.com/rss/articles/CBMirAFBVV95cUxOS2ZFSlhpUDZueldBUXpTQ1MtZ3QwX0l1bjhsQzAxRjF1ZnhQOHNDcTA4VzM0a3FKQ0pSRUY3Q2JCa3lVTnBxU29jLU5Gd2Rnb2stQmxnSl95MDNVZGlCSHVJZVFfQWp1azR3UnNOU3pkZjlXTW1ESTU4V0lMdy1RbFRLUC10anpoUUpwZ0dKc2E2VVdvUDBCb2tQbHRLSTNrcW8zMHJiMGdmNHJC?oc=5" target="_blank">Fair decisions, clear reasons: Creating Fuzzy AI with fairness built in from the start</a> <font color="#6f6f6f">Asia Research News |</font>
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Assessing Pause Thresholds for empirical Translation Process Research
arXiv:2604.01410v1 Announce Type: new Abstract: Text production (and translations) proceeds in the form of stretches of typing, interrupted by keystroke pauses. It is often assumed that fast typing reflects unchallenged/automated translation production while long(er) typing pauses are indicative of translation problems, hurdles or difficulties. Building on a long discussion concerning the determination of pause thresholds that separate automated from presumably reflective translation processes (O'Brien, 2006; Alves and Vale, 2009; Timarova et al., 2011; Dragsted and Carl, 2013; Lacruz et al., 2014; Kumpulainen, 2015; Heilmann and Neumann 2016), this paper compares three recent approaches for computing these pause thresholds, and suggest and evaluate a novel method for computing Production
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