--- title: "Workshop on Gender Bias in Natural Language Processing 2024" description: "Workshop on Gender Bias in Natural Language Processing 2024 — accepted papers: 1 paper in the Elamur Research library (Bangkok…" canonical: "https://research.elamur.ai/free/en/venues/gebnlp/2024/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/venues/gebnlp/2024/) [home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [Workshop on Gender Bias in Natural…](https://md.research.elamur.ai/free/en/venues/gebnlp/) / 2024 # 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](https://md.research.elamur.ai/free/en/countries/thailand/) · 🗓 August 2024 [**26** papers in the proceedings](#all) · [**1** work in our library](https://md.research.elamur.ai/free/en/venues/gebnlp/2024/#works) · [**2** citations of these works](https://md.research.elamur.ai/free/en/venues/gebnlp/2024/#works) ## 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 Path](https://md.research.elamur.ai/free/en/papers/gupta-2023-sociodemographic-bias-language-models-survey/)**Vipul 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 ↗](https://aclanthology.org/2024.gebnlp-1.7/)**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 ↗](https://aclanthology.org/2024.gebnlp-1.16/)**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 ↗](https://aclanthology.org/2024.gebnlp-1.18/)**Marion Bartl, Susan Leavy*6 citations* 5. **[An Empirical Study of Gendered Stereotypes in Emotional Attributes for Bangla in Multilingual Large Language Models ↗](https://aclanthology.org/2024.gebnlp-1.25/)**Jayanta Sadhu, Maneesha Saha, Rifat Shahriyar*4 citations* 6. **[Stop! In the Name of Flaws: Disentangling Personal Names and Sociodemographic Attributes in NLP ↗](https://aclanthology.org/2024.gebnlp-1.20/)**Vagrant Gautam, Arjun Subramonian, Anne Lauscher et al.*4 citations* 7. **[Towards Fairer NLP Models: Handling Gender Bias In Classification Tasks ↗](https://aclanthology.org/2024.gebnlp-1.10/)**Nasim Sobhani, Sarah Delany*4 citations* 8. **[We Don't Talk About That: Case Studies on Intersectional Analysis of Social Bias in Large Language Models ↗](https://aclanthology.org/2024.gebnlp-1.3/)**Hannah Devinney, Jenny Björklund, Henrik Björklund*4 citations* 9. **[Evaluating Gender Bias in Multilingual Multimodal AI Models: Insights from an Indian Context ↗](https://aclanthology.org/2024.gebnlp-1.21/)**Kshitish Ghate, Arjun Choudhry, Vanya Bannihatti Kumar*3 citations* 10. **[A Parameter-Efficient Multi-Objective Approach to Mitigate Stereotypical Bias in Language Models ↗](https://aclanthology.org/2024.gebnlp-1.1/)**Yifan Wang, Vera Demberg*2 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 Path](https://md.research.elamur.ai/free/en/papers/gupta-2023-sociodemographic-bias-language-models-survey/)**Vipul 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 ↗](https://aclanthology.org/2024.gebnlp-1.7/)**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 ↗](https://aclanthology.org/2024.gebnlp-1.16/)**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 ↗](https://aclanthology.org/2024.gebnlp-1.18/)**Marion Bartl, Susan Leavy*6 citations* 5. **[An Empirical Study of Gendered Stereotypes in Emotional Attributes for Bangla in Multilingual Large Language Models ↗](https://aclanthology.org/2024.gebnlp-1.25/)**Jayanta Sadhu, Maneesha Saha, Rifat Shahriyar*4 citations* 6. **[Stop! In the Name of Flaws: Disentangling Personal Names and Sociodemographic Attributes in NLP ↗](https://aclanthology.org/2024.gebnlp-1.20/)**Vagrant Gautam, Arjun Subramonian, Anne Lauscher et al.*4 citations* 7. **[Towards Fairer NLP Models: Handling Gender Bias In Classification Tasks ↗](https://aclanthology.org/2024.gebnlp-1.10/)**Nasim Sobhani, Sarah Delany*4 citations* 8. **[We Don't Talk About That: Case Studies on Intersectional Analysis of Social Bias in Large Language Models ↗](https://aclanthology.org/2024.gebnlp-1.3/)**Hannah Devinney, Jenny Björklund, Henrik Björklund*4 citations* 9. **[Evaluating Gender Bias in Multilingual Multimodal AI Models: Insights from an Indian Context ↗](https://aclanthology.org/2024.gebnlp-1.21/)**Kshitish Ghate, Arjun Choudhry, Vanya Bannihatti Kumar*3 citations* 10. **[A Parameter-Efficient Multi-Objective Approach to Mitigate Stereotypical Bias in Language Models ↗](https://aclanthology.org/2024.gebnlp-1.1/)**Yifan Wang, Vera Demberg*2 citations* 11. **[Dissecting Biases in Relation Extraction: A Cross-Dataset Analysis on People's Gender and Origin ↗](https://aclanthology.org/2024.gebnlp-1.12/)**Marco Stranisci, Pere-Lluís Huguet Cabot, Elisa Bassignana et al.*2 citations* 12. **[Investigating Gender Bias in STEM Job Advertisements ↗](https://aclanthology.org/2024.gebnlp-1.11/)**Malika Dikshit, Houda Bouamor, Nizar Habash*2 citations* 13. **[Whose wife is it anyway? Assessing bias against same-gender relationships in machine translation ↗](https://aclanthology.org/2024.gebnlp-1.23/)**Ian Stewart, Rada Mihalcea*2 citations* 14. **[A Fairness Analysis of Human and AI-Generated Student Reflection Summaries ↗](https://aclanthology.org/2024.gebnlp-1.5/)**Bhiman Kumar Baghel, Arun Balajiee Lekshmi Narayanan, Michael Miller Yoder*1 citation* 15. **[An Explainable Approach to Understanding Gender Stereotype Text ↗](https://aclanthology.org/2024.gebnlp-1.4/)**Manuela Jeyaraj, Sarah Delany*1 citation* 16. **[Analysis of Annotator Demographics in Sexism Detection ↗](https://aclanthology.org/2024.gebnlp-1.24/)**Narjes Tahaei, Sabine Bergler*1 citation* 17. **[Detecting Gender Discrimination on Actor Level Using Linguistic Discourse Analysis ↗](https://aclanthology.org/2024.gebnlp-1.8/)**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 ↗](https://aclanthology.org/2024.gebnlp-1.13/)**Duygu Altinok*1 citation* 19. **[Generating Gender Alternatives in Machine Translation ↗](https://aclanthology.org/2024.gebnlp-1.15/)**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 ↗](https://aclanthology.org/2024.gebnlp-1.9/)**Hongyu Chen, Michael Roth, Agnieszka Falenska*1 citation* 21. **[Detecting and Mitigating LGBTQIA+ Bias in Large Norwegian Language Models ↗](https://aclanthology.org/2024.gebnlp-1.22/)**Selma Bergstrand, Björn Gambäck 22. **[Disagreeable, Slovenly, Honest and Un-named Women? Investigating Gender Bias in English Educational Resources by Extending Existing Gender Bias Taxonomies](https://md.research.elamur.ai/free/en/papers/zhu-2024-disagreeable-slovenly-honest-un-named/)**Haotian 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 ↗](https://aclanthology.org/2024.gebnlp-1.2/)**Shucheng Zhu, Bingjie Du, Jishun Zhao et al. 24. **[Is there Gender Bias in Dependency Parsing? Revisiting “Women's Syntactic Resilience” ↗](https://aclanthology.org/2024.gebnlp-1.17/)**Paul Go, Agnieszka Falenska 25. **[On Shortcuts and Biases: How Finetuned Language Models Distinguish Audience-Specific Instructions in Italian and English ↗](https://aclanthology.org/2024.gebnlp-1.6/)**Nicola Fanton, Michael Roth [See all 26 papers in Workshop on Gender Bias in Natural Language Processing 2024 — accepted papers →](https://md.research.elamur.ai/free/en/venues/gebnlp/2024/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 Taxonomies](https://md.research.elamur.ai/free/en/papers/zhu-2024-disagreeable-slovenly-honest-un-named/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Haotian 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)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [English (1)](https://md.research.elamur.ai/free/en/topics/english/) ## Fields [Social Sciences (1)](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. [🧑‍🔬**Fei Xia**1 work here · 2 citations](https://md.research.elamur.ai/free/en/authors/fei-xia/) · [🧑‍🔬**Haotian Zhu**1 work here · 2 citations](https://md.research.elamur.ai/free/en/authors/haotian-zhu/) · [🧑‍🔬**Kexin Gao**1 work here · 2 citations](https://md.research.elamur.ai/free/en/authors/kexin-gao/) · [🧑‍🔬**Mari Ostendorf**1 work here · 2 citations](https://md.research.elamur.ai/free/en/authors/mari-ostendorf/) ## Top institutions Institutions on the bylines of its works here, by the number of works. [🎓**University of Washington** Seattle · United States 1 work here](https://md.research.elamur.ai/free/en/universities/university-of-washington/) 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 2023](https://md.research.elamur.ai/free/en/venues/gebnlp/2023/) - [next → Workshop on Gender Bias in Natural Language Processing 2025](https://md.research.elamur.ai/free/en/venues/gebnlp/2025/) - [↑ back to Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)