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Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases
  in Word Embeddings But do not Remove Them

Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them

9 March 2019
Hila Gonen
Yoav Goldberg
ArXivPDFHTML

Papers citing "Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them"

50 / 308 papers shown
Title
A Survey on Bias and Fairness in Natural Language Processing
A Survey on Bias and Fairness in Natural Language Processing
Rajas Bansal
SyDa
17
14
0
06 Mar 2022
Welcome to the Modern World of Pronouns: Identity-Inclusive Natural
  Language Processing beyond Gender
Welcome to the Modern World of Pronouns: Identity-Inclusive Natural Language Processing beyond Gender
Anne Lauscher
Archie Crowley
Dirk Hovy
AILaw
29
54
0
24 Feb 2022
Investigations of Performance and Bias in Human-AI Teamwork in Hiring
Investigations of Performance and Bias in Human-AI Teamwork in Hiring
Andi Peng
Besmira Nushi
Emre Kıcıman
K. Inkpen
Ece Kamar
14
29
0
21 Feb 2022
XAI for Transformers: Better Explanations through Conservative
  Propagation
XAI for Transformers: Better Explanations through Conservative Propagation
Ameen Ali
Thomas Schnake
Oliver Eberle
G. Montavon
Klaus-Robert Muller
Lior Wolf
FAtt
15
89
0
15 Feb 2022
Counterfactual Multi-Token Fairness in Text Classification
Counterfactual Multi-Token Fairness in Text Classification
P. Lohia
21
3
0
08 Feb 2022
Kernelized Concept Erasure
Kernelized Concept Erasure
Shauli Ravfogel
Francisco Vargas
Yoav Goldberg
Ryan Cotterell
24
32
0
28 Jan 2022
Linear Adversarial Concept Erasure
Linear Adversarial Concept Erasure
Shauli Ravfogel
Michael Twiton
Yoav Goldberg
Ryan Cotterell
KELM
84
57
0
28 Jan 2022
Gender Bias in Text: Labeled Datasets and Lexicons
Gender Bias in Text: Labeled Datasets and Lexicons
Jad Doughman
Wael Khreich
32
8
0
21 Jan 2022
Regional Negative Bias in Word Embeddings Predicts Racial Animus--but
  only via Name Frequency
Regional Negative Bias in Word Embeddings Predicts Racial Animus--but only via Name Frequency
Austin Van Loon
Salvatore Giorgi
Robb Willer
J. Eichstaedt
42
10
0
20 Jan 2022
Millions of Co-purchases and Reviews Reveal the Spread of Polarization
  and Lifestyle Politics across Online Markets
Millions of Co-purchases and Reviews Reveal the Spread of Polarization and Lifestyle Politics across Online Markets
Alex Ruch
Ari Decter-Frain
Raghav Batra
11
2
0
17 Jan 2022
Pretrained Language Models for Text Generation: A Survey
Pretrained Language Models for Text Generation: A Survey
Junyi Li
Tianyi Tang
Wayne Xin Zhao
J. Nie
Ji-Rong Wen
AI4CE
36
128
0
14 Jan 2022
Privacy-aware Early Detection of COVID-19 through Adversarial Training
Privacy-aware Early Detection of COVID-19 through Adversarial Training
Omid Rohanian
Samaneh Kouchaki
A. Soltan
Jenny Yang
Morteza Rohanian
Yang Yang
David A. Clifton
AAML
OOD
31
6
0
09 Jan 2022
A Survey on Gender Bias in Natural Language Processing
A Survey on Gender Bias in Natural Language Processing
Karolina Stañczak
Isabelle Augenstein
30
110
0
28 Dec 2021
Degendering Resumes for Fair Algorithmic Resume Screening
Degendering Resumes for Fair Algorithmic Resume Screening
Prasanna Parasurama
João Sedoc
FaML
17
3
0
16 Dec 2021
Measuring Fairness with Biased Rulers: A Survey on Quantifying Biases in
  Pretrained Language Models
Measuring Fairness with Biased Rulers: A Survey on Quantifying Biases in Pretrained Language Models
Pieter Delobelle
E. Tokpo
T. Calders
Bettina Berendt
19
24
0
14 Dec 2021
Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic
  Information Preserving
Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving
Lei Ding
Dengdeng Yu
Jinhan Xie
Wenxing Guo
Shenggang Hu
Meichen Liu
Linglong Kong
Hongsheng Dai
Yanchun Bao
Bei Jiang
FaML
19
30
0
09 Dec 2021
Evaluating Metrics for Bias in Word Embeddings
Evaluating Metrics for Bias in Word Embeddings
Sarah Schröder
Alexander Schulz
Philip Kenneweg
Robert Feldhans
Fabian Hinder
Barbara Hammer
21
10
0
15 Nov 2021
Feature and Label Embedding Spaces Matter in Addressing Image Classifier
  Bias
Feature and Label Embedding Spaces Matter in Addressing Image Classifier Bias
William Thong
Cees G. M. Snoek
22
14
0
27 Oct 2021
Fairness in Missing Data Imputation
Fairness in Missing Data Imputation
Yiliang Zhang
Q. Long
36
12
0
22 Oct 2021
The Arabic Parallel Gender Corpus 2.0: Extensions and Analyses
The Arabic Parallel Gender Corpus 2.0: Extensions and Analyses
Bashar Alhafni
Nizar Habash
Houda Bouamor
25
18
0
18 Oct 2021
Improving Gender Fairness of Pre-Trained Language Models without
  Catastrophic Forgetting
Improving Gender Fairness of Pre-Trained Language Models without Catastrophic Forgetting
Zahra Fatemi
Chen Xing
Wenhao Liu
Caiming Xiong
CLL
29
33
0
11 Oct 2021
On a Benefit of Mask Language Modeling: Robustness to Simplicity Bias
On a Benefit of Mask Language Modeling: Robustness to Simplicity Bias
Ting-Rui Chiang
32
4
0
11 Oct 2021
Multi-Objective Few-shot Learning for Fair Classification
Multi-Objective Few-shot Learning for Fair Classification
Ishani Mondal
Procheta Sen
Debasis Ganguly
FaML
18
4
0
05 Oct 2021
Unpacking the Interdependent Systems of Discrimination: Ableist Bias in
  NLP Systems through an Intersectional Lens
Unpacking the Interdependent Systems of Discrimination: Ableist Bias in NLP Systems through an Intersectional Lens
Saad Hassan
Matt Huenerfauth
Cecilia Ovesdotter Alm
48
38
0
01 Oct 2021
Second Order WinoBias (SoWinoBias) Test Set for Latent Gender Bias
  Detection in Coreference Resolution
Second Order WinoBias (SoWinoBias) Test Set for Latent Gender Bias Detection in Coreference Resolution
Hillary Dawkins
14
0
0
28 Sep 2021
Marked Attribute Bias in Natural Language Inference
Marked Attribute Bias in Natural Language Inference
Hillary Dawkins
52
8
0
28 Sep 2021
Language Invariant Properties in Natural Language Processing
Language Invariant Properties in Natural Language Processing
Federico Bianchi
Debora Nozza
Dirk Hovy
55
3
0
27 Sep 2021
Uncovering Implicit Gender Bias in Narratives through Commonsense
  Inference
Uncovering Implicit Gender Bias in Narratives through Commonsense Inference
Tenghao Huang
Faeze Brahman
Vered Shwartz
Snigdha Chaturvedi
AI4CE
8
31
0
14 Sep 2021
NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic
  Rewriting into Gender-Neutral Alternatives
NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender-Neutral Alternatives
Eva Vanmassenhove
Chris Emmery
D. Shterionov
23
51
0
13 Sep 2021
How Does Fine-tuning Affect the Geometry of Embedding Space: A Case
  Study on Isotropy
How Does Fine-tuning Affect the Geometry of Embedding Space: A Case Study on Isotropy
S. Rajaee
Mohammad Taher Pilehvar
79
20
0
10 Sep 2021
Assessing the Reliability of Word Embedding Gender Bias Measures
Assessing the Reliability of Word Embedding Gender Bias Measures
Yupei Du
Qixiang Fang
D. Nguyen
46
21
0
10 Sep 2021
Debiasing Methods in Natural Language Understanding Make Bias More
  Accessible
Debiasing Methods in Natural Language Understanding Make Bias More Accessible
Michael J. Mendelson
Yonatan Belinkov
42
23
0
09 Sep 2021
Hi, my name is Martha: Using names to measure and mitigate bias in
  generative dialogue models
Hi, my name is Martha: Using names to measure and mitigate bias in generative dialogue models
Eric Michael Smith
Adina Williams
32
28
0
07 Sep 2021
Social Norm Bias: Residual Harms of Fairness-Aware Algorithms
Social Norm Bias: Residual Harms of Fairness-Aware Algorithms
Myra Cheng
Maria De-Arteaga
Lester W. Mackey
Adam Tauman Kalai
FaML
32
7
0
25 Aug 2021
Diachronic Analysis of German Parliamentary Proceedings: Ideological
  Shifts through the Lens of Political Biases
Diachronic Analysis of German Parliamentary Proceedings: Ideological Shifts through the Lens of Political Biases
Tobias Walter
Celina Kirschner
Steffen Eger
Goran Glavavs
Anne Lauscher
Simone Paolo Ponzetto
16
20
0
13 Aug 2021
On Measures of Biases and Harms in NLP
On Measures of Biases and Harms in NLP
Sunipa Dev
Emily Sheng
Jieyu Zhao
Aubrie Amstutz
Jiao Sun
...
M. Sanseverino
Jiin Kim
Akihiro Nishi
Nanyun Peng
Kai-Wei Chang
31
80
0
07 Aug 2021
Using Adversarial Debiasing to Remove Bias from Word Embeddings
Using Adversarial Debiasing to Remove Bias from Word Embeddings
Dana Kenna
FaML
27
4
0
21 Jul 2021
Debiasing Multilingual Word Embeddings: A Case Study of Three Indian
  Languages
Debiasing Multilingual Word Embeddings: A Case Study of Three Indian Languages
Srijan Bansal
Vishal Garimella
Ayush Suhane
Animesh Mukherjee
30
9
0
21 Jul 2021
Trustworthy AI: A Computational Perspective
Trustworthy AI: A Computational Perspective
Haochen Liu
Yiqi Wang
Wenqi Fan
Xiaorui Liu
Yaxin Li
Shaili Jain
Yunhao Liu
Anil K. Jain
Jiliang Tang
FaML
104
196
0
12 Jul 2021
Quantifying Social Biases in NLP: A Generalization and Empirical
  Comparison of Extrinsic Fairness Metrics
Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metrics
Paula Czarnowska
Yogarshi Vyas
Kashif Shah
21
104
0
28 Jun 2021
A Source-Criticism Debiasing Method for GloVe Embeddings
A Source-Criticism Debiasing Method for GloVe Embeddings
Hope McGovern
30
2
0
25 Jun 2021
Evaluating Gender Bias in Hindi-English Machine Translation
Evaluating Gender Bias in Hindi-English Machine Translation
Gauri Gupta
Krithika Ramesh
Sanjay Singh
19
22
0
16 Jun 2021
Modeling Profanity and Hate Speech in Social Media with Semantic
  Subspaces
Modeling Profanity and Hate Speech in Social Media with Semantic Subspaces
Vanessa Hahn
Dana Ruiter
Thomas Kleinbauer
Dietrich Klakow
8
7
0
14 Jun 2021
Obtaining Better Static Word Embeddings Using Contextual Embedding
  Models
Obtaining Better Static Word Embeddings Using Contextual Embedding Models
Prakhar Gupta
Martin Jaggi
11
30
0
08 Jun 2021
RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of
  Conversational Language Models
RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models
Soumya Barikeri
Anne Lauscher
Ivan Vulić
Goran Glavas
45
178
0
07 Jun 2021
Ethical-Advice Taker: Do Language Models Understand Natural Language
  Interventions?
Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions?
Jieyu Zhao
Daniel Khashabi
Tushar Khot
Ashish Sabharwal
Kai-Wei Chang
KELM
26
49
0
02 Jun 2021
Bangla Natural Language Processing: A Comprehensive Analysis of
  Classical, Machine Learning, and Deep Learning Based Methods
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods
Ovishake Sen
Mohtasim Fuad
Md. Nazrul Islam
Jakaria Rabbi
Mehedi Masud
...
Md. Abdul Awal
Awal Ahmed Fime
Md. Tahmid Hasan Fuad
Delowar Sikder
Md. Akil Raihan Iftee
11
39
0
31 May 2021
Evaluating Gender Bias in Natural Language Inference
Evaluating Gender Bias in Natural Language Inference
Shanya Sharma
Manan Dey
Koustuv Sinha
28
41
0
12 May 2021
What's in the Box? A Preliminary Analysis of Undesirable Content in the
  Common Crawl Corpus
What's in the Box? A Preliminary Analysis of Undesirable Content in the Common Crawl Corpus
A. Luccioni
J. Viviano
35
114
0
06 May 2021
Fair Representation Learning for Heterogeneous Information Networks
Fair Representation Learning for Heterogeneous Information Networks
Ziqian Zeng
Rashidul Islam
Kamrun Naher Keya
James R. Foulds
Yangqiu Song
Shimei Pan
32
40
0
18 Apr 2021
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