Papers by Andrea Vallebueno

1 papers
Statistical Uncertainty in Word Embeddings: GloVe-V (2024.emnlp-main)

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Challenge: Static word embeddings are ubiquitous in computational social science applications . however, assessing the statistical uncertainty in downstream conclusions remains challenging .
Approach: They propose a method to obtain approximate, easy-to-use, and scalable reconstruction error variance estimates for one of the most widely used word embedding models.
Outcome: The proposed method enables hypothesis testing in key word embedding tasks.

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