51 citations · 83 across the 10 of their papers we have counts for
6 papers · 1 filter
Dehumanizing Machines: Mitigating Anthropomorphic Behaviors in Text Generation Systems
Myra Cheng, Su Lin Blodgett, Alicia DeVrio +2
As text generation systems' outputs are increasingly anthropomorphic -- perceived as human-like -- scholars have also increasingly raised concerns about how such outputs can lead t…
Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications
Kaitlyn Zhou, Su Lin Blodgett, Adam Trischler +3
There are many ways to express similar things in text, which makes evaluating natural language generation (NLG) systems difficult. Compounding this difficulty is the need to assess…
A Survey of Race, Racism, and Anti-Racism in NLP
Anjalie Field, Su Lin Blodgett, Zeerak Waseem +1
Despite inextricable ties between race and language, little work has considered race in NLP research and development. In this work, we survey 79 papers from the ACL anthology that…
How to Write a Bias Statement: Recommendations for Submissions to the Workshop on Gender Bias in NLP
Christian Hardmeier, Marta R. Costa-jussà, Kellie Webster +2
At the Workshop on Gender Bias in NLP (GeBNLP), we'd like to encourage authors to give explicit consideration to the wider aspects of bias and its social implications. For the 2020…
Language (Technology) is Power: A Critical Survey of "Bias" in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé +1
We survey 146 papers analyzing "bias" in NLP systems, finding that their motivations are often vague, inconsistent, and lacking in normative reasoning, despite the fact that analyz…
Monte Carlo Syntax Marginals for Exploring and Using Dependency Parses
Katherine A. Keith, Su Lin Blodgett, Brendan O'Connor
Dependency parsing research, which has made significant gains in recent years, typically focuses on improving the accuracy of single-tree predictions. However, ambiguity is inheren…