Papers by Damián Blasi

7 papers
Modeling the Unigram Distribution (2021.findings-acl)

Copied to clipboard

Challenge: a novel model for estimating the unigram distribution is proposed for a language . the model is based on the word type and word type distributions, but does not consider contextual information.
Approach: They propose a neuralization of Goldwater's (2011) model for estimating the unigram distribution in a language.
Outcome: The proposed model outperforms character-level models in estimating the unigram distribution in a language.
On the Interpretability and Significance of Bias Metrics in Texts: a PMI-based Approach (2023.acl-short)

Copied to clipboard

Challenge: Word embeddings have been used to quantify biases in texts for years, but their statistical properties and advantages have not been studied.
Approach: They propose to use PMI-based metric to quantify bias in corpora by conditional probabilities and odds ratio to approximate it.
Outcome: The proposed measure can be approximated by an odds ratio, which makes statistical inferences cost-effective and meaningful.
Finding Concept-specific Biases in Form–Meaning Associations (2021.naacl-main)

Copied to clipboard

Challenge: Existing methods to detect cross-linguistic associations are not effective, but their effects are minor.
Approach: They propose a method to measure cross-linguistic associations by controlling for the influence of language family and geographic proximity within a large concept-aligned, cross-lingual lexicon.
Outcome: The proposed method shows that it is small, but it is unsurprisingly small (less than 0.5% on average).
How (Non-)Optimal is the Lexicon? (2021.naacl-main)

Copied to clipboard

Challenge: lexical meanings are mapped to wordforms by usage pressures and constraints on sequences of symbols.
Approach: They propose a coding-theoretic view of the lexicon and a novel generative statistical model to quantify its compressibility under various constraints.
Outcome: The proposed model shows that (compositional) morphology and graphotactics can account for most of the complexity of natural codes—as measured by code length.
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs (2021.tacl-1)

Copied to clipboard

Challenge: In many languages, nouns possess grammatical genders.
Approach: They use large-scale corpora and tools from NLP and information theory to test whether there is a relationship between grammatical genders of inanimate nouns and adjectives used to describe them.
Outcome: The results show that there is a statistically significant relationship between the grammatical genders of inanimate nouns and adjectives used to describe them in all six languages.
Evaluating Word Embeddings with Categorical Modularity (2021.findings-acl)

Copied to clipboard

Challenge: Existing word embeddings use different bilingual supervision signals with varying levels of strength.
Approach: They propose a graph modularity metric to measure word embedding quality . they use a set of 500 words belonging to 59 neurobiologically motivated semantic categories .
Outcome: The proposed metric measures word embedding quality on monolingual and cross-lingual tasks.
A surprisal–duration trade-off across and within the world’s languages (2021.emnlp-main)

Copied to clipboard

Challenge: Throughout human evolution, countless languages have evolved, each with unique features.
Approach: They analysed a corpus of 600 languages to find strong evidence for a surprisal–duration trade-off between languages and languages.
Outcome: The proposed model shows that phones are produced faster in languages where they are less surprising and vice versa.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations