Cross-lingual Pronoun Prediction with Linguistically Informed Features

UnMASKed: Quantifying Gender Biases in Masked Language Models through Linguistically Informed Job Market Prompts

Language models (LMs) have become pivotal in the realm of technological advancements. While their capabilities are vast and transformative, they often include societal biases encoded in the human-produced datasets used f…

Linguistically-Informed Multilingual Instruction Tuning: Is There an Optimal Set of Languages to Tune?

Multilingual language models often perform unevenly across different languages due to limited generalization capabilities for some languages. This issue is significant because of the growing interest in making universal …

Multilingual BERT has an accent: Evaluating English influences on fluency in multilingual models

While multilingual language models can improve NLP performance on low-resource languages by leveraging higher-resource languages, they also reduce average performance on all languages (the 'curse of multilinguality'). He…

Pronoun-Focused MT and Cross-Lingual Pronoun Prediction: Findings of the 2015 DiscoMT Shared Task on Pronoun Translation

Neural Machine Translation for Cross-Lingual Pronoun Prediction

In this paper we present our systems for the DiscoMT 2017 cross-lingual pronoun prediction shared task. For all four language pairs, we trained a standard attention-based neural machine translation system as well as thre…