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Yulia Tsvetkov

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.SI1
ORCID 0000-0002-4634-7128
same name
  • Yulia Tsvetkov — 5 papers, h 37

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedMeasuring Bias in Contextualized Word Representations

19 citations · 23 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2019

CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology

Aditi Chaudhary, Elizabeth Salesky, Gayatri Bhat +3

This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lem…

cs.CL2019★ 19 cited

Measuring Bias in Contextualized Word Representations

Keita Kurita, Nidhi Vyas, Ayush Pareek +2

Contextual word embeddings such as BERT have achieved state of the art performance in numerous NLP tasks. Since they are optimized to capture the statistical properties of training…

cs.SI2019

Contextual Affective Analysis: A Case Study of People Portrayals in Online #MeToo Stories

Anjalie Field, Gayatri Bhat, Yulia Tsvetkov

In October 2017, numerous women accused producer Harvey Weinstein of sexual harassment. Their stories encouraged other women to voice allegations of sexual harassment against many…

cs.CL2019★ 4 cited

Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings

Thomas Manzini, Yao Chong Lim, Yulia Tsvetkov +1

Online texts -- across genres, registers, domains, and styles -- are riddled with human stereotypes, expressed in overt or subtle ways. Word embeddings, trained on these texts, per…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.