This is a collection of natural language processing papers that deal with bias (mostly gender bias). The list is by no means complete and is just a way to keep up with the large amount of papers in that area. If you miss a paper, please add it.
Towards Detection of Subjective Bias using Contextualized Word Embeddings
WebConf2020 - Paper, Code
Note: Wikineutrality Corpus.
Joint Multiclass Debiasing of Word Embeddings
ISMIS2020 - Paper, Code
Note: Hard and Soft WEAT
Towards Debiasing Sentence Representations
ACL2020 - Paper, Code
Note: Sentence-level debiasing. Difference between pretraining and finetuning.
Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation
arxiv2020 - Paper
Note: Counterfactual generation.
Unsupervised Discovery of Implicit Gender Bias
arxiv2020 - Paper, Code
Note: Unsupervised bias detection from comments.
StereoSet: Measuring stereotypical bias in pretrained language models
arxiv2020 - Paper, Code
Note: Benchmark and Dataset for measuring bias in 4 domains (gender, profession, race, religion).
Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation
ACL2020 - Paper, Code
Note: Double Hard Debias: mitigigate dataset and then do debiasing
Gender Bias in Multilingual Embeddings and Cross-Lingual Transfer
ACL2020 - Paper
Note: Bias in multilingual embeddings depends on the alignment direction.
Scalable Cross Lingual Pivots to Model Pronoun Gender for Translation
arxiv2020 - Paper
Note: Gender labels for pronouns in MT English-Spanish.
Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases
arxiv2020 - Paper
Note: CEAT
OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings
arxiv2020 - Paper
Note: Preserve semantic meaning of embeddings.
Investigating Gender Bias in BERT
arxiv2020 - Paper
Note: Identify one gender direction per BERT layer.
Type B Reflexivization as an Unambiguous Testbed for Multilingual Multi-Task Gender Bias
arxiv2020 - Paper, Code
Note: Multilingual multitask dataset across 4 languages.
Towards Debiasing NLU Models from Unknown Biases
arxiv2020 - Paper, Code
Note: Unsupervised bias detection.
Robustness and Reliability of Gender Bias Assessment in Word Embeddings: The Role of Base Pairs
arxiv2020 - Paper, Code
Note: Choice of base pairs is relevant.
LOGAN: Local Group Bias Detection by Clustering
arxiv2020 - Paper
Note: Identify biases through clustering.
Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation
arxiv2020 - Paper
Note: Verify whether non-linear debiasing helps. It seems not.
Unmasking Contextual Stereotypes: Measuring and Mitigating BERT’s Gender Bias
GeBNLP2020 - Paper, Code
Note: Verify gender debiasing techniques in German.
Language (Technology) is Power: A Critical Survey of “Bias” in NLP
arxiv2020 - Paper
Note: Metastudy: survey of 146 gender bias papers
Pick a Fight or Bite your Tongue: Investigation of Gender Differences in Idiomatic Language Usage
arxiv2020 - Paper
Note: Idiomatic expressions depending on the speaker.
Evaluating Bias In Dutch Word Embeddings
GeBNLP2020 - Paper, Code
Note: Examining bias in Dutch (using WEAT)
Analyzing Gender Bias within Narrative Tropes
arxiv2020 - Paper, Code
Note: Analyze bias using tropes
Neural Machine Translation Doesn’t Translate Gender Coreference Right Unless You Make It
GeBNLP2020 - Paper, Code
Note: Incorporate explicit word-level gender tags.
The Gap on GAP: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets
NeurIPS 2020 - Paper, Code
Note: Distances in GAP play a role.
AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddings
arxiv2020 - Paper, Code
Note: Arabic WEAT.
Characterising Bias in Compressed Models
arxiv2020 - Paper
Note: Bias in compressed model is large. Provide method to identify biased examples.
Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them
NAACL2019 - Paper, Code
Note: Debiasing by setting dimensions to zero ist not effective
Equalizing Gender Bias in Neural Machine Translation with Word Embeddings Techniques
GeBNLP 2019 - Paper
Note: Spanisch-Englisch translation with occupations.
Evaluating the Underlying Gender Bias in Contextualized Word Embeddings
GeBNLP 2019 - Paper
Note: Cointextualized embeddings are less biased than static ones.
Mitigating Gender Bias in Natural Language Processing: Literature Review
ACL2019 - Paper
Note: Survey
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes
NAACL2019 - Paper
Note: Work on biographies.
Assessing Social and Intersectional Biases in Contextualized Word Representations
NeurIPS2019 - Paper
Note: Strong bias in contextualized embeddings. Bias not always visible on sentence level.
It’s All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution
EMNLP2019 - Paper
Note: Counterfactual Data Substitution (CDS)
Good Secretaries, Bad Truck Drivers? Occupational Gender Stereotypes in Sentiment Analysis
GeBNLP 2019 - Paper, Code
Note: Dataset of 800 sentences analysed with sentiment analysis.
Automatic Gender Identification and Reinflection in Arabic
GeBNLP 2019 - Paper
Note: Arabic English Translation with focus on getting the pronouns right.
Gendered Ambiguous Pronouns Shared Task: Boosting Model Confidence by Evidence Pooling
GeBNLP 2019 - Paper, Code
Note: Shared task winner GAP
Gendered Ambiguous Pronouns (GAP) Shared Task at the Gender Bias in NLP Workshop 2019
GeBNLP 2019 - Paper, Code
Note: GAP shared task description
Conceptor Debiasing of Word Representations Evaluated on WEAT
GeBNLP 2019 - Paper
Note: Proposes Conceptor Debiasing.
On Measuring Gender Bias in Translation of Gender-neutral Pronouns
GeBNLP 2019 - Paper, Code
Note: Gender bias in pronoun translation Korean-English
Measuring Gender Bias in Word Embeddings across Domains and Discovering New Gender Bias Word Categories
GeBNLP 2019 - Paper, Code
Note: Clustering method for discovering new biases.
The Role of Protected Class Word Lists in Bias Identification of Contextualized Word Representations
GeBNLP 2019 - Paper
Note: Uses conceptor debiasing
The Woman Worked as a Babysitter: On Biases in Language Generation
EMNLP2019 - Paper, Code
Note: Regard and Sentiment. Annotations released.
Exploring Human Gender Stereotypes with Word Association Test
EMNLP2019 - Paper, Code
Note: Word association graphs
Gender-preserving Debiasing for Pre-trained Word Embeddings
ACL2019 - Paper, Code
Note: Differentiate between bias and gender information.
Quantifying Social Biases in Contextual Word Representations
GeBNLP 2019 - Paper
Note: Template based method to quantify bias.
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
ACM Fat 2019 - Paper
Note: Analyze effects of bias.
Gender Bias in Neural Natural Language Processing
Logic, Language, and Security. Springer. 2018 - Paper
Note: Counterfactual Data Augmentation (CDA). Clear definition of Bias. Evaluates on coreference resolution and language modelling.
Gender Bias in Coreference Resolution
NAACL2018 - Paper, Code
Note: Windogender schemes.
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
NeurIPS2016 - Paper, Code
Note: Among the first to address gender bias
Rejecting the Gender Binary: A Vector-Space Operation.
2015 - Paper
Note: Blog post: first to propose to remove gender dimension
TODOS
- add https://arxiv.org/pdf/2011.12086.pdf
- add https://arxiv.org/pdf/2011.12096.pdf
- add papers from GeBNLP2020 once they are available.