4 citations · 4 across the 3 of their papers we have counts for
4 papers
Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metrics
Paula Czarnowska, Yogarshi Vyas, Kashif Shah
Measuring bias is key for better understanding and addressing unfairness in NLP/ML models. This is often done via fairness metrics which quantify the differences in a model's behav…
Morphologically Aware Word-Level Translation
Paula Czarnowska, Sebastian Ruder, Ryan Cotterell +1
We propose a novel morphologically aware probability model for bilingual lexicon induction, which jointly models lexeme translation and inflectional morphology in a structured way.…
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
Ekaterina Vylomova, Jennifer White, Elizabeth Salesky +25
A broad goal in natural language processing (NLP) is to develop a system that has the capacity to process any natural language. Most systems, however, are developed using data from…
Don't Forget the Long Tail! A Comprehensive Analysis of Morphological Generalization in Bilingual Lexicon Induction
Paula Czarnowska, Sebastian Ruder, Edouard Grave +2
Human translators routinely have to translate rare inflections of words - due to the Zipfian distribution of words in a language. When translating from Spanish, a good translator w…