📰 Workshop on Gender Bias in Natural Language Processing 2020 — accepted papers

Workshop on Gender Bias in Natural Language Processing 2020 is the 2020 edition of the Workshop on Gender Bias in Natural Language Processing, held in Barcelona, Spain (Online), December 2020 (publisher: Association for Computational Linguistics). The ACL Anthology lists 12 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.

All accepted papers (12)

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

1. Can Existing Methods Debias Languages Other than English? First Attempt to Analyze and Mitigate Japanese Word Embeddings ↗Masashi Takeshita, Yuki Katsumata, Rafal Rzepka et al.
2. Conversational Assistants and Gender Stereotypes: Public Perceptions and Desiderata for Voice Personas ↗Amanda Cercas Curry, Judy Robertson, Verena Rieser
3. Evaluating Bias In Dutch Word Embeddings ↗Rodrigo Alejandro Chávez Mulsa, Gerasimos Spanakis
4. Fine-tuning Neural Machine Translation on Gender-Balanced Datasets ↗Marta R. Costa-jussà, Adrià de Jorge
5. Gender and sentiment, critics and authors: a dataset of Norwegian book reviews ↗Samia Touileb, Lilja Øvrelid, Erik Velldal
6. Gender-Aware Reinflection using Linguistically Enhanced Neural Models ↗Bashar Alhafni, Nizar Habash, Houda Bouamor
7. Interdependencies of Gender and Race in Contextualized Word Embeddings ↗May Jiang, Christiane Fellbaum
8. Investigating Societal Biases in a Poetry Composition System ↗Emily Sheng, David Uthus
9. Neural Machine Translation Doesn't Translate Gender Coreference Right Unless You Make ItDanielle Saunders, Rosie Sallis, Bill Byrneour summary
10. Semi-Supervised Topic Modeling for Gender Bias Discovery in English and Swedish ↗Hannah Devinney, Jenny Björklund, Henrik Björklund
11. Situated Data, Situated Systems: A Methodology to Engage with Power Relations in Natural Language Processing Research ↗Lucy Havens, Melissa Terras, Benjamin Bach et al.
12. Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender BiasMarion Bartl, Malvina Nissim, Albert Gattour summary

📄 Papers with our summary in our library (2)

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

1. Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender BiasWorkshop on Gender Bias in Natural Language ProcessingMarion Bartl, Malvina Nissim, Albert Gatt2020 · 115 citations
2. Neural Machine Translation Doesn't Translate Gender Coreference Right Unless You Make ItWorkshop on Gender Bias in Natural Language ProcessingDanielle Saunders, Rosie Sallis, Bill Byrne2020 · 86 citations

🧭 Top topics

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

🔗Coreference resolution (1)🔁Machine translation (1)🛡️Bias, fairness & safety (1)

📚 Fields

🎭Arts and Humanities (2)🖥️Computer Science (2)🤝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 GroningenGroningen · Netherlands1 work here🎓University of MaltaMsida · Malta1 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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This page in Markdown → https://md.research.elamur.ai/free/en/venues/gebnlp/2020/