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title: "Workshop on Gender Bias in Natural Language Processing 2022"
description: "Workshop on Gender Bias in Natural Language Processing 2022 — accepted papers: 2 papers in the Elamur Research library (Seattle…"
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# Workshop on Gender Bias in Natural Language Processing 2022 — accepted papers

Workshop on Gender Bias in Natural Language Processing 2022 is the 2022 edition of the Workshop on Gender Bias in Natural Language Processing, held in Seattle, Washington, July 2022 (publisher: Association for Computational Linguistics). The ACL Anthology lists 28 papers of it; our library holds 2 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

📍 Seattle, Washington · 🗓 July 2022

[**28** papers in the proceedings](#all) · [**2** works in our library](https://md.research.elamur.ai/free/en/venues/gebnlp/2022/#works) · [**33** citations of these works](https://md.research.elamur.ai/free/en/venues/gebnlp/2022/#works)

## Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. **[Worst of Both Worlds: Biases Compound in Pre-trained Vision-and-Language Models ↗](https://aclanthology.org/2022.gebnlp-1.10/)**Tejas Srinivasan, Yonatan Bisk*31 citations*
2. **[Gender Bias in BERT - Measuring and Analysing Biases through Sentiment Rating in a Realistic Downstream Classification Task ↗](https://aclanthology.org/2022.gebnlp-1.20/)**Sophie Jentzsch, Cigdem Turan*29 citations*
3. **[Looking for a Handsome Carpenter! Debiasing GPT-3 Job Advertisements ↗](https://aclanthology.org/2022.gebnlp-1.22/)**Conrad Borchers, Dalia Gala, Benjamin Gilburt et al.*24 citations*
4. **[Choose Your Lenses: Flaws in Gender Bias Evaluation ↗](https://aclanthology.org/2022.gebnlp-1.17/)**Hadas Orgad, Yonatan Belinkov*18 citations*
5. **[Challenges in Measuring Bias via Open-Ended Language Generation ↗](https://aclanthology.org/2022.gebnlp-1.9/)**Afra Feyza Akyürek, Muhammed Yusuf Kocyigit, Sejin Paik et al.*17 citations*
6. **[Fewer Errors, but More Stereotypes? The Effect of Model Size on Gender Bias ↗](https://aclanthology.org/2022.gebnlp-1.13/)**Yarden Tal, Inbal Magar, Roy Schwartz*15 citations*
7. **[Why Knowledge Distillation Amplifies Gender Bias and How to Mitigate from the Perspective of DistilBERT ↗](https://aclanthology.org/2022.gebnlp-1.27/)**Jaimeen Ahn, Hwaran Lee, Jinhwa Kim et al.*15 citations*
8. **[Gender Biases and Where to Find Them: Exploring Gender Bias in Pre-Trained Transformer-based Language Models Using Movement Pruning ↗](https://aclanthology.org/2022.gebnlp-1.6/)**Przemyslaw Joniak, Akiko Aizawa*12 citations*
9. **[Gendered Language in Resumes and its Implications for Algorithmic Bias in Hiring ↗](https://aclanthology.org/2022.gebnlp-1.7/)**Prasanna Parasurama, João Sedoc*12 citations*
10. **[Don't Forget About Pronouns: Removing Gender Bias in Language Models Without Losing Factual Gender Information ↗](https://aclanthology.org/2022.gebnlp-1.3/)**Tomasz Limisiewicz, David Mareček*11 citations*

## All accepted papers (28)

The most cited first; 2 with our summary link to their page here, the others to the original.

1. **[Worst of Both Worlds: Biases Compound in Pre-trained Vision-and-Language Models ↗](https://aclanthology.org/2022.gebnlp-1.10/)**Tejas Srinivasan, Yonatan Bisk*31 citations*
2. **[Gender Bias in BERT - Measuring and Analysing Biases through Sentiment Rating in a Realistic Downstream Classification Task ↗](https://aclanthology.org/2022.gebnlp-1.20/)**Sophie Jentzsch, Cigdem Turan*29 citations*
3. **[Looking for a Handsome Carpenter! Debiasing GPT-3 Job Advertisements ↗](https://aclanthology.org/2022.gebnlp-1.22/)**Conrad Borchers, Dalia Gala, Benjamin Gilburt et al.*24 citations*
4. **[Choose Your Lenses: Flaws in Gender Bias Evaluation ↗](https://aclanthology.org/2022.gebnlp-1.17/)**Hadas Orgad, Yonatan Belinkov*18 citations*
5. **[Challenges in Measuring Bias via Open-Ended Language Generation ↗](https://aclanthology.org/2022.gebnlp-1.9/)**Afra Feyza Akyürek, Muhammed Yusuf Kocyigit, Sejin Paik et al.*17 citations*
6. **[Fewer Errors, but More Stereotypes? The Effect of Model Size on Gender Bias ↗](https://aclanthology.org/2022.gebnlp-1.13/)**Yarden Tal, Inbal Magar, Roy Schwartz*15 citations*
7. **[Why Knowledge Distillation Amplifies Gender Bias and How to Mitigate from the Perspective of DistilBERT ↗](https://aclanthology.org/2022.gebnlp-1.27/)**Jaimeen Ahn, Hwaran Lee, Jinhwa Kim et al.*15 citations*
8. **[Gender Biases and Where to Find Them: Exploring Gender Bias in Pre-Trained Transformer-based Language Models Using Movement Pruning ↗](https://aclanthology.org/2022.gebnlp-1.6/)**Przemyslaw Joniak, Akiko Aizawa*12 citations*
9. **[Gendered Language in Resumes and its Implications for Algorithmic Bias in Hiring ↗](https://aclanthology.org/2022.gebnlp-1.7/)**Prasanna Parasurama, João Sedoc*12 citations*
10. **[Don't Forget About Pronouns: Removing Gender Bias in Language Models Without Losing Factual Gender Information ↗](https://aclanthology.org/2022.gebnlp-1.3/)**Tomasz Limisiewicz, David Mareček*11 citations*
11. **[Analyzing Hate Speech Data along Racial, Gender and Intersectional Axes ↗](https://aclanthology.org/2022.gebnlp-1.1/)**Antonis Maronikolakis, Philip Baader, Hinrich Schütze*9 citations*
12. **[Occupational Biases in Norwegian and Multilingual Language Models ↗](https://aclanthology.org/2022.gebnlp-1.21/)**Samia Touileb, Lilja Øvrelid, Erik Velldal*9 citations*
13. **[The Birth of Bias: A case study on the evolution of gender bias in an English language model](https://md.research.elamur.ai/free/en/papers/wal-2022-birth-bias-case-study-evolution/)**Oskar Van Der Wal, Jaap Jumelet, Katrin Schulz et al.*8 citations · our summary*
14. **[Mitigating Gender Stereotypes in Hindi and Marathi ↗](https://aclanthology.org/2022.gebnlp-1.16/)**Neeraja Kirtane, Tanvi Anand*7 citations*
15. **[Uncertainty and Inclusivity in Gender Bias Annotation: An Annotation Taxonomy and Annotated Datasets of British English Text](https://md.research.elamur.ai/free/en/papers/havens-2022-uncertainty-inclusivity-gender-bias-annotation/)**Lucy Havens, Melissa Terras, Benjamin Bach et al.*7 citations · our summary*
16. **[An Empirical Study on the Fairness of Pre-trained Word Embeddings ↗](https://aclanthology.org/2022.gebnlp-1.15/)**Emeralda Sesari, Max Hort, Federica Sarro*6 citations*
17. **[Unsupervised Mitigating Gender Bias by Character Components: A Case Study of Chinese Word Embedding ↗](https://aclanthology.org/2022.gebnlp-1.14/)**Xiuying Chen, Mingzhe Li, Rui Yan et al.*6 citations*
18. **[A Taxonomy of Bias-Causing Ambiguities in Machine Translation ↗](https://aclanthology.org/2022.gebnlp-1.18/)**Michal Měchura*5 citations*
19. **[Indigenous Language Revitalization and the Dilemma of Gender Bias ↗](https://aclanthology.org/2022.gebnlp-1.25/)**Oussama Hansal, Ngoc Tan Le, Fatiha Sadat*5 citations*
20. **[Debiasing Neural Retrieval via In-batch Balancing Regularization ↗](https://aclanthology.org/2022.gebnlp-1.5/)**Yuantong Li, Xiaokai Wei, Zijian Wang et al.*4 citations*
21. **[Analysis of Gender Bias in Social Perception and Judgement Using Chinese Word Embeddings ↗](https://aclanthology.org/2022.gebnlp-1.2/)**Jiali Li, Shucheng Zhu, Ying Liu et al.*3 citations*
22. **[Evaluating Gender Bias Transfer from Film Data ↗](https://aclanthology.org/2022.gebnlp-1.24/)**Amanda Bertsch, Ashley Oh, Sanika Natu et al.*3 citations*
23. **[Incorporating Subjectivity into Gendered Ambiguous Pronoun (GAP) Resolution using Style Transfer ↗](https://aclanthology.org/2022.gebnlp-1.28/)**Kartikey Pant, Tanvi Dadu*3 citations*
24. **[What changed? Investigating Debiasing Methods using Causal Mediation Analysis ↗](https://aclanthology.org/2022.gebnlp-1.26/)**Sullam Jeoung, Jana Diesner*3 citations*
25. **[Assessing Group-level Gender Bias in Professional Evaluations: The Case of Medical Student End-of-Shift Feedback ↗](https://aclanthology.org/2022.gebnlp-1.11/)**Emmy Liu, Michael Henry Tessler, Nicole Dubosh et al.*2 citations*

[See all 28 papers in Workshop on Gender Bias in Natural Language Processing 2022 — accepted papers →](https://md.research.elamur.ai/free/en/venues/gebnlp/2022/papers/)

## Papers with our summary in our library (2)

The most cited first (OpenAlex citations plus our library's).

1. **[The Birth of Bias: A case study on the evolution of gender bias in an English language model](https://md.research.elamur.ai/free/en/papers/wal-2022-birth-bias-case-study-evolution/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Oskar Van Der Wal, Jaap Jumelet, Katrin Schulz, et al.*2022 · 19 citations*
2. **[Uncertainty and Inclusivity in Gender Bias Annotation: An Annotation Taxonomy and Annotated Datasets of British English Text](https://md.research.elamur.ai/free/en/papers/havens-2022-uncertainty-inclusivity-gender-bias-annotation/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Lucy Havens, Melissa Terras, Benjamin Bach, et al.*2022 · 14 citations*

## Top topics

Topics of its works in our library, with the number of works on each.

[Bias, fairness & safety (2)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [English (2)](https://md.research.elamur.ai/free/en/topics/english/) · [Language models & pretraining (1)](https://md.research.elamur.ai/free/en/topics/language-models/)

## Fields

[Arts and Humanities (2)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science (2)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Social Sciences (2)](https://md.research.elamur.ai/free/en/shelves/social-sciences/)

## Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

[🧑‍🔬**Jaap Jumelet**1 work here · 19 citations](https://md.research.elamur.ai/free/en/authors/jaap-jumelet/) · [🧑‍🔬**Oskar van der Wal**1 work here · 19 citations](https://md.research.elamur.ai/free/en/authors/oskar-van-der-wal/) · [🧑‍🔬**Willem Zuidema**1 work here · 19 citations](https://md.research.elamur.ai/free/en/authors/willem-zuidema/) · [🧑‍🔬**Beatrice Alex**1 work here · 14 citations](https://md.research.elamur.ai/free/en/authors/beatrice-alex/) · [🧑‍🔬**Benjamin Bach**1 work here · 14 citations](https://md.research.elamur.ai/free/en/authors/benjamin-bach/) · [🧑‍🔬**Lucy Havens**1 work here · 14 citations](https://md.research.elamur.ai/free/en/authors/lucy-havens/) · [🧑‍🔬**Melissa Terras**1 work here · 14 citations](https://md.research.elamur.ai/free/en/authors/melissa-terras/)

## Top institutions

Institutions on the bylines of its works here, by the number of works.

[🎓**University of Amsterdam** Amsterdam · Netherlands 1 work here](https://md.research.elamur.ai/free/en/universities/university-of-amsterdam/) · [🎓**University of Edinburgh** Edinburgh · United Kingdom 1 work here](https://md.research.elamur.ai/free/en/universities/university-of-edinburgh/)

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

- [← previous Workshop on Gender Bias in Natural Language Processing 2020](https://md.research.elamur.ai/free/en/venues/gebnlp/2020/)
- [next → Workshop on Gender Bias in Natural Language Processing 2023](https://md.research.elamur.ai/free/en/venues/gebnlp/2023/)
- [↑ back to Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)