📰 Workshop on Gender Bias in Natural Language Processing 2024 — accepted papers

Workshop on Gender Bias in Natural Language Processing 2024 is the 2024 edition of the Workshop on Gender Bias in Natural Language Processing, held in Bangkok, Thailand, August 2024 (publisher: Association for Computational Linguistics). The ACL Anthology lists 26 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

📍 Bangkok, Thailand · 🗓 August 2024

Most cited papers

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

1. Sociodemographic Bias in Language Models: A Survey and Forward PathVipul Gupta, Pranav Narayanan Venkit, Shomir Wilson et al.13 citations · our summary
2. The power of Prompts: Evaluating and Mitigating Gender Bias in MT with LLMs ↗Aleix Sant, Carlos Escolano, Audrey Mash et al.8 citations
3. Beyond Binary Gender Labels: Revealing Gender Bias in LLMs through Gender-Neutral Name Predictions ↗Zhiwen You, HaeJin Lee, Shubhanshu Mishra et al.6 citations
4. From `Showgirls' to `Performers': Fine-tuning with Gender-inclusive Language for Bias Reduction in LLMs ↗Marion Bartl, Susan Leavy6 citations
5. An Empirical Study of Gendered Stereotypes in Emotional Attributes for Bangla in Multilingual Large Language Models ↗Jayanta Sadhu, Maneesha Saha, Rifat Shahriyar4 citations
6. Stop! In the Name of Flaws: Disentangling Personal Names and Sociodemographic Attributes in NLP ↗Vagrant Gautam, Arjun Subramonian, Anne Lauscher et al.4 citations
7. Towards Fairer NLP Models: Handling Gender Bias In Classification Tasks ↗Nasim Sobhani, Sarah Delany4 citations
8. We Don't Talk About That: Case Studies on Intersectional Analysis of Social Bias in Large Language Models ↗Hannah Devinney, Jenny Björklund, Henrik Björklund4 citations
9. Evaluating Gender Bias in Multilingual Multimodal AI Models: Insights from an Indian Context ↗Kshitish Ghate, Arjun Choudhry, Vanya Bannihatti Kumar3 citations
10. A Parameter-Efficient Multi-Objective Approach to Mitigate Stereotypical Bias in Language Models ↗Yifan Wang, Vera Demberg2 citations

All accepted papers (26)

The most cited first; 1 with our summary link to their page here, the others to the original.

1. Sociodemographic Bias in Language Models: A Survey and Forward PathVipul Gupta, Pranav Narayanan Venkit, Shomir Wilson et al.13 citations · our summary
2. The power of Prompts: Evaluating and Mitigating Gender Bias in MT with LLMs ↗Aleix Sant, Carlos Escolano, Audrey Mash et al.8 citations
3. Beyond Binary Gender Labels: Revealing Gender Bias in LLMs through Gender-Neutral Name Predictions ↗Zhiwen You, HaeJin Lee, Shubhanshu Mishra et al.6 citations
4. From `Showgirls' to `Performers': Fine-tuning with Gender-inclusive Language for Bias Reduction in LLMs ↗Marion Bartl, Susan Leavy6 citations
5. An Empirical Study of Gendered Stereotypes in Emotional Attributes for Bangla in Multilingual Large Language Models ↗Jayanta Sadhu, Maneesha Saha, Rifat Shahriyar4 citations
6. Stop! In the Name of Flaws: Disentangling Personal Names and Sociodemographic Attributes in NLP ↗Vagrant Gautam, Arjun Subramonian, Anne Lauscher et al.4 citations
7. Towards Fairer NLP Models: Handling Gender Bias In Classification Tasks ↗Nasim Sobhani, Sarah Delany4 citations
8. We Don't Talk About That: Case Studies on Intersectional Analysis of Social Bias in Large Language Models ↗Hannah Devinney, Jenny Björklund, Henrik Björklund4 citations
9. Evaluating Gender Bias in Multilingual Multimodal AI Models: Insights from an Indian Context ↗Kshitish Ghate, Arjun Choudhry, Vanya Bannihatti Kumar3 citations
10. A Parameter-Efficient Multi-Objective Approach to Mitigate Stereotypical Bias in Language Models ↗Yifan Wang, Vera Demberg2 citations
11. Dissecting Biases in Relation Extraction: A Cross-Dataset Analysis on People's Gender and Origin ↗Marco Stranisci, Pere-Lluís Huguet Cabot, Elisa Bassignana et al.2 citations
12. Investigating Gender Bias in STEM Job Advertisements ↗Malika Dikshit, Houda Bouamor, Nizar Habash2 citations
13. Whose wife is it anyway? Assessing bias against same-gender relationships in machine translation ↗Ian Stewart, Rada Mihalcea2 citations
14. A Fairness Analysis of Human and AI-Generated Student Reflection Summaries ↗Bhiman Kumar Baghel, Arun Balajiee Lekshmi Narayanan, Michael Miller Yoder1 citation
15. An Explainable Approach to Understanding Gender Stereotype Text ↗Manuela Jeyaraj, Sarah Delany1 citation
16. Analysis of Annotator Demographics in Sexism Detection ↗Narjes Tahaei, Sabine Bergler1 citation
17. Detecting Gender Discrimination on Actor Level Using Linguistic Discourse Analysis ↗Stefanie Urchs, Veronika Thurner, Matthias Aßenmacher et al.1 citation
18. Gender Bias in Turkish Word Embeddings: A Comprehensive Study of Syntax, Semantics and Morphology Across Domains ↗Duygu Altinok1 citation
19. Generating Gender Alternatives in Machine Translation ↗Sarthak Garg, Mozhdeh Gheini, Clara Emmanuel et al.1 citation
20. What Can Go Wrong in Authorship Profiling: Cross-Domain Analysis of Gender and Age Prediction ↗Hongyu Chen, Michael Roth, Agnieszka Falenska1 citation
21. Detecting and Mitigating LGBTQIA+ Bias in Large Norwegian Language Models ↗Selma Bergstrand, Björn Gambäck
22. Disagreeable, Slovenly, Honest and Un-named Women? Investigating Gender Bias in English Educational Resources by Extending Existing Gender Bias TaxonomiesHaotian Zhu, Kexin Gao, Fei Xia et al.our summary
23. Do PLMs and Annotators Share the Same Gender Bias? Definition, Dataset, and Framework of Contextualized Gender Bias ↗Shucheng Zhu, Bingjie Du, Jishun Zhao et al.
24. Is there Gender Bias in Dependency Parsing? Revisiting “Women's Syntactic Resilience” ↗Paul Go, Agnieszka Falenska
25. On Shortcuts and Biases: How Finetuned Language Models Distinguish Audience-Specific Instructions in Italian and English ↗Nicola Fanton, Michael Roth

See all 26 papers in Workshop on Gender Bias in Natural Language Processing 2024 — accepted papers →

📄 Papers with our summary in our library (1)

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

1. Disagreeable, Slovenly, Honest and Un-named Women? Investigating Gender Bias in English Educational Resources by Extending Existing Gender Bias TaxonomiesWorkshop on Gender Bias in Natural Language ProcessingHaotian Zhu, Kexin Gao, Fei Xia, et al.2024 · 2 citations

🧭 Top topics

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

🛡️Bias, fairness & safety (1)English (1)

📚 Fields

🤝Social Sciences (1)

🧑‍🔬 Top authors

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

🏛️ Top institutions

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

🎓University of WashingtonSeattle · United States1 work here

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

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