3 citations · 6 across the 5 of their papers we have counts for
7 papers · 1 filter
Systematic Inequalities in Language Technology Performance across the World's Languages
Damián Blasi, Antonios Anastasopoulos, Graham Neubig
Natural language processing (NLP) systems have become a central technology in communication, education, medicine, artificial intelligence, and many other domains of research and de…
A surprisal--duration trade-off across and within the world's languages
Tiago Pimentel, Clara Meister, Elizabeth Salesky +3
While there exist scores of natural languages, each with its unique features and idiosyncrasies, they all share a unifying theme: enabling human communication. We may thus reasonab…
Modeling the Unigram Distribution
Irene Nikkarinen, Tiago Pimentel, Damián E. Blasi +1
The unigram distribution is the non-contextual probability of finding a specific word form in a corpus. While of central importance to the study of language, it is commonly approxi…
Evaluating Word Embeddings with Categorical Modularity
Sílvia Casacuberta, Karina Halevy, Damián E. Blasi
We introduce categorical modularity, a novel low-resource intrinsic metric to evaluate word embedding quality. Categorical modularity is a graph modularity metric based on the -…
How (Non-)Optimal is the Lexicon?
Tiago Pimentel, Irene Nikkarinen, Kyle Mahowald +2
The mapping of lexical meanings to wordforms is a major feature of natural languages. While usage pressures might assign short words to frequent meanings (Zipf's law of abbreviatio…
Finding Concept-specific Biases in Form--Meaning Associations
Tiago Pimentel, Brian Roark, Søren Wichmann +2
This work presents an information-theoretic operationalisation of cross-linguistic non-arbitrariness. It is not a new idea that there are small, cross-linguistic associations betwe…
On the Interpretability and Significance of Bias Metrics in Texts: a PMI-based Approach
Francisco Valentini, Germán Rosati, Damián Blasi +2
In recent years, word embeddings have been widely used to measure biases in texts. Even if they have proven to be effective in detecting a wide variety of biases, metrics based on…