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The rapid growth of Large Language Models (LLMs) has put forward the study of biases as a crucial field.
CrowS-pairs: A challenge dataset for measuring social biases in masked language models
Nikita Nangia, Clara Vania, Rasika Bhalerao, and Samuel R. Bowman. 2020 · 1967
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Bias in computer systems
Batya Friedman and Helen Nissenbaum. 1996 · 1996
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Certifying and removing disparate impact
Michael Feldman, Sorelle A. Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian. 2015 · 2015
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Man is to computer programmer as woman is to homemaker? debiasing word embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, and Adam Kalai. 2016 · 2016
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Gender bias in coreference resolution
Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme. 2018 · 2018
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Personalizing dialogue agents: I have a dog, do you have pets too?
Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston. 2018 · 2018
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Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2018 · 2018
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The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng. 2019 · 2019
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A critical review on women oppression and threats in private spheres: Bangladesh perspective
Nishat Tarannum. 2019 · 2019
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Language (technology) is power: A critical survey of “bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, and Hanna Wallach. 2020 · 2020
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The state and fate of linguistic diversity and inclusion in the NLP world
Pratik Joshi, Sebastin Santy, Amar Budhiraja, Kalika Bali, and Monojit Choudhury. 2020 · 2020
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Persistent anti-muslim bias in large language models
Abubakar Abid, Maheen Farooqi, and James Zou. 2021 · 2021
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XL-sum: Large-scale multilingual abstractive summarization for 44 languages
Tahmid Hasan, Abhik Bhattacharjee, Md. Saiful Islam, Kazi Mubasshir, Yuan-Fang Li, Yong-Bin Kang, M. Sohel Rahman, and Rifat Shahriyar. 2021 · 2021
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Uncovering implicit gender bias in narratives through commonsense inference
Tenghao Huang, Faeze Brahman, Vered Shwartz, and Snigdha Chaturvedi. 2021 · 2021
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A psychological study on the differences in attitude toward oppression among different generations of adult women in west bengal
N. Jain, M. Ghosh, and S. Saha. 2021 · 2021
Cited alongside, same era.
Gender and representation bias in GPT-3 generated stories
Li Lucy and David Bamman. 2021 · 2021
Cited alongside, same era.
StereoSet: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy. 2021 · 2021
Cited alongside, same era.
A survey on gender bias in natural language processing
Karolina Stanczak and Isabelle Augenstein. 2021 · 2021
Cited alongside, same era.
BanglaParaphrase: A high-quality Bangla paraphrase dataset
Ajwad Akil, Najrin Sultana, Abhik Bhattacharjee, and Rifat Shahriyar. 2022 · 2022
Cited alongside, same era.
Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023
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Chatgpt for good? on opportunities and challenges of large language models for education
Enkelejda Kasneci, Kathrin Sessler, Stefan Küchemann, Maria Bannert, Daryna Dementieva, Frank Fischer, Urs Gasser, Georg Groh, Stephan Günnemann, Eyke Hüllermeier, Stephan Krusche, Gitta Kutyniok, Tilman Michaeli, Claudia Nerdel, Jürgen Pfeffer, Oleksandra Poquet, Michael Sailer, Albrecht Schmidt, Tina Seidel, Matthias Stadler, Jochen Weller, Jochen Kuhn, and Gjergji Kasneci. 2023 · 2023
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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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Biases in large language models: Origins, inventory, and discussion
Roberto Navigli, Simone Conia, and Björn Ross. 2023 · 2023
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An analysis of social biases present in BERT variants across multiple languages
Parishad BehnamGhader and Aristides Milios. 2022 · 2022
Cited alongside, same era.
BanglaBERT: Language model pretraining and benchmarks for low-resource language understanding evaluation in Bangla
Abhik Bhattacharjee, Tahmid Hasan, Wasi Ahmad, Kazi Samin Mubasshir, Md Saiful Islam, Anindya Iqbal, M. Sohel Rahman, and Rifat Shahriyar. 2022 · 2022
Cited alongside, same era.
Mitigating gender bias in distilled language models via counterfactual role reversal
Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, and Aram Galstyan. 2022 · 2022
Cited alongside, same era.
Taxonomy of risks posed by language models
Laura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, Po-Sen Huang, John Mellor, Amelia Glaese, Myra Cheng, Borja Balle, Atoosa Kasirzadeh, Courtney Biles, Sasha Brown, Zac Kenton, Will Hawkins, Tom Stepleton, Abeba Birhane, Lisa Anne Hendricks, Laura Rimell, William Isaac, Julia Haas, Sean Legassick, Geoffrey Irving, and Iason Gabriel. 2022 · 2022
Cited alongside, same era.
Probing pre-trained language models for cross-cultural differences in values
Arnav Arora, Lucie-aimée Kaffee, and Isabelle Augenstein. 2023 · 2023
Cited alongside, same era.
CrossSum: Beyond English-centric cross-lingual summarization for 1,500+ language pairs
Abhik Bhattacharjee, Tahmid Hasan, Wasi Uddin Ahmad, Yuan-Fang Li, Yong-Bin Kang, and Rifat Shahriyar. 2023 · 2023
Cited alongside, same era.
Toward cultural bias evaluation datasets: The case of Bengali gender, religious, and national identity
Dipto Das, Shion Guha, and Bryan Semaan. 2023 · 2023
Cited alongside, same era.
Shantipriya Parida, Sambit Sekhar, Subhadarshi Panda, Soumendra Kumar Sahoo, Swateek Jena, Abhijeet Parida, Arghyadeep Sen, Satya Ranjan Dash, and Deepak Kumar Pradhan. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
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On evaluating and mitigating gender biases in multilingual settings
Aniket Vashishtha, Kabir Ahuja, and Sunayana Sitaram. 2023 · 2023
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Llama 3 model card
AI@Meta. 2024 · 2024
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Self-debiasing large language models: Zero-shot recognition and reduction of stereotypes
Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, Md Mehrab Tanjim, Tong Yu, Hanieh Deilamsalehy, Ruiyi Zhang, Sungchul Kim, and Franck Dernoncourt. 2024 · 2024
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A trip towards fairness: Bias and de-biasing in large language models
Leonardo Ranaldi, Elena Ruzzetti, Davide Venditti, Dario Onorati, and Fabio Zanzotto. 2024 · 2024
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An empirical study on the characteristics of bias upon context length variation for Bangla
Jayanta Sadhu, Ayan Khan, Abhik Bhattacharjee, and Rifat Shahriyar. 2024 · 2024
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IndiBias: A benchmark dataset to measure social biases in language models for Indian context
Nihar Sahoo, Pranamya Kulkarni, Arif Ahmad, Tanu Goyal, Narjis Asad, Aparna Garimella, and Pushpak Bhattacharyya. 2024 · 2024
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Large language models are not robust multiple choice selectors
Chujie Zheng, Hao Zhou, Fandong Meng, Jie Zhou, and Minlie Huang. 2024 · 2024
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