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Large language models (LLMs) often inherit and amplify social biases embedded in their training data.
Gender across languages: The linguistic representation of women and men, Vol. 1
Marlis Ed Hellinger and Hadumod Ed Bußmann. 2001 · 2001
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Europarl: A parallel corpus for statistical machine translation
Philipp Koehn. 2005 · 2005
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Representation of the sexes in language
Dagmar Stahlberg, Friederike Braun, Lisa Irmen, and Sabine Sczesny. 2007 · 2007
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The gendering of language: A comparison of gender equality in countries with gendered, natural gender, and genderless languages
Jennifer L Prewitt-Freilino, T Andrew Caswell, and Emmi K Laakso. 2012 · 2012
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Parallel data, tools and interfaces in OPUS
Jörg Tiedemann. 2012 · 2012
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The social impact of natural language processing
Dirk Hovy and Shannon L Spruit. 2016 · 2016
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Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J Bryson, and Arvind Narayanan. 2017 · 2017
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Men also like shopping: Reducing gender bias amplification using corpus-level constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2017 · 2017
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Biostatistics: A Foundation for Analysis in the Health Sciences
Wayne W Daniel and Chad L Cross. 2018 · 2018
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Data analytics and algorithmic bias in policing
Alexander Babuta and Marion Oswald. 2019 · 2019
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Fairness and Machine Learning: Limitations and Opportunities
Solon Barocas, Moritz Hardt, and Arvind Narayanan. 2019 · 2019
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Understanding the origins of bias in word embeddings
Marc-Etienne Brunet, Colleen Alkalay-Houlihan, Ashton Anderson, and Richard Zemel. 2019 · 2019
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How does grammatical gender affect noun representations in gender-marking languages?
Hila Gonen, Yova Kementchedjhieva, and Yoav Goldberg. 2019 · 2019
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Global Voices: Crossing borders in automatic news summarization
Khanh Nguyen and Hal Daumé III. 2019 · 2019
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Artificial intelligence and algorithmic bias: Implications for health systems
Trishan Panch, Heather Mattie, and Rifat Atun. 2019 · 2019
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Gendered languages may play a role in limiting women’s opportunities
World Bank Group. 2019 · 2019
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CCAligned: A massive collection of cross-lingual web-document pairs
Ahmed El-Kishky, Vishrav Chaudhary, Francisco Guzmán, and Philipp Koehn. 2020 · 2020
A survey on gender bias in natural language processing
Karolina Stańczak and Isabelle Augenstein. 2021 · 2021
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Quality at a glance: An audit of web-crawled multilingual datasets
Julia Kreutzer, Isaac Caswell, Lisa Wang, Ahsan Wahab, Daan van Esch, Nasanbayar Ulzii-Orshikh, Allahsera Auguste Tapo, Nishant Subramani, Artem Sokolov, Claytone Sikasote, et al. 2022 · 2022
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Measuring gender bias in word embeddings of gendered languages requires disentangling grammatical gender signals
Shiva Omrani Sabbaghi and Aylin Caliskan. 2022 · 2022
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Gender bias and stereotypes in large language models
Hadas Kotek, Rikker Dockum, and David Sun. 2023 · 2023
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Quantifying gender bias towards politicians in cross-lingual language models
Karolina Stańczak, Sagnik Ray Choudhury, Tiago Pimentel, Ryan Cotterell, and Isabelle Augenstein. 2023 · 2023
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Mitigating bias in algorithmic hiring: Evaluating claims and practices
Manish Raghavan, Solon Barocas, Jon Kleinberg, and Karen Levy. 2020 · 2020
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Towards cross-lingual generalization of translation gender bias
Won Ik Cho, Jiwon Kim, Jaeyeong Yang, and Nam Soo Kim. 2021 · 2021
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BOLD: Dataset and metrics for measuring biases in open-ended language generation
Jwala Dhamala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, and Rahul Gupta. 2021 · 2021
Cited alongside, same era.
Shirtless and dangerous: Quantifying linguistic signals of gender bias in an online fiction writing community
Ethan Fast, Tina Vachovsky, and Michael Bernstein. 2021 · 2021
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On the relationship of social gender equality and grammatical gender in pre-trained large language models
Magdalena Biesialska, David Solans, Jordi Luque, and Carlos Segura. 2024 · 2024
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QLoRA: Efficient finetuning of quantized LLMs
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2024 · 2024
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Bias and fairness in large language models: A survey
Isabel O Gallegos, Ryan A Rossi, Joe Barrow, Md Mehrab Tanjim, Sungchul Kim, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, and Nesreen K Ahmed. 2024 · 2024
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Gender bias in transformers: A comprehensive review of detection and mitigation strategies
Praneeth Nemani, Yericherla Deepak Joel, Palla Vijay, and Farhana Ferdouzi Liza. 2024 · 2024
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Man made language models? Evaluating LLMs’ perpetuation of masculine generics bias
Enzo Doyen and Amalia Todirascu. 2025 · 2025
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