34 citations · 75 across the 13 of their papers we have counts for
4 papers · 1 filter
Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?
Ivan Vulić, Goran Glavaš, Roi Reichart +1
Recent efforts in cross-lingual word embedding (CLWE) learning have predominantly focused on fully unsupervised approaches that project monolingual embeddings into a shared cross-l…
A General Framework for Implicit and Explicit Debiasing of Distributional Word Vector Spaces
Anne Lauscher, Goran Glavaš, Simone Paolo Ponzetto +1
Distributional word vectors have recently been shown to encode many of the human biases, most notably gender and racial biases, and models for attenuating such biases have conseque…
Are We Consistently Biased? Multidimensional Analysis of Biases in Distributional Word Vectors
Anne Lauscher, Goran Glavaš
Word embeddings have recently been shown to reflect many of the pronounced societal biases (e.g., gender bias or racial bias). Existing studies are, however, limited in scope and d…
How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions
Goran Glavas, Robert Litschko, Sebastian Ruder +1
Cross-lingual word embeddings (CLEs) enable multilingual modeling of meaning and facilitate cross-lingual transfer of NLP models. Despite their ubiquitous usage in downstream tasks…