Fetching the paper…
Reading the bibliography…
In the current landscape of automatic language generation, there is a need to understand, evaluate, and mitigate demographic biases as existing models are becoming increasingly multilingual.
chrf: character n-gram f-score for automatic mt evaluation
Maja Popović · 2015
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2018
Earlier work this paper cites.
Semantics derived automatically from language corpora contain human-like moral choices
Sophie Jentzsch, Patrick Schramowski, Constantin Rothkopf, and Kristian Kersting · 2019
Earlier work this paper cites.
Measuring bias in contextualized word representations
Keita Kurita, Nidhi Vyas, Ayush Pareek, Alan W Black, and Yulia Tsvetkov · 2019
Earlier work this paper cites.
On measuring social biases in sentence encoders
Chandler May, Alex Wang, Shikha Bordia, Samuel Bowman, and Rachel Rudinger · 2019
Earlier work this paper cites.
The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Prem Natarajan, and Nanyun Peng · 2019
Earlier work this paper cites.
Evaluating gender bias in machine translation
Gabriel Stanovsky, Noah A. Smith, and Luke Zettlemoyer · 2019
Earlier work this paper cites.
Measuring and reducing gendered correlations in pre-trained models, 2020
Kellie Webster, Xuezhi Wang, Ian Tenney, Alex Beutel, Emily Pitler, Ellie Pavlick, Jilin Chen, and Slav Petrov · 2020
Earlier work this paper cites.
DIALOGPT : Large-scale generative pre-training for conversational response generation
Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, and Bill Dolan · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
Collecting a large-scale gender bias dataset for coreference resolution and machine translation
Shahar Levy, Koren Lazar, and Gabriel Stanovsky · 2021
Earlier work this paper cites.
Gender bias amplification during speed-quality optimization in neural machine translation
Adithya Renduchintala, Denise Diaz, Kenneth Heafield, Xian Li, and Mona Diab · 2021
Cited alongside, same era.
Gender bias in machine translation
Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi · 2021
Cited alongside, same era.
A robustly optimized BERT pre-training approach with post-training
Liu Zhuang, Lin Wayne, Shi Ya, and Zhao Jun · 2021
Cited alongside, same era.
The Arabic parallel gender corpus 2.0: Extensions and analyses
Bashar Alhafni, Nizar Habash, and Houda Bouamor · 2022
Cited alongside, same era.
Gender bias in multilingual neural machine translation: The architecture matters
Marta R. Costa-jussà, Carlos Escolano, Christine Basta, Javier Ferrando, Roser Batlle, and Ksenia Kharitonova · 2022
Cited alongside, same era.
Seamlessm4t: Massively multilingual & multimodal machine translation, 2023
Seamless Communication, Loïc Barrault, Yu-An Chung, Mariano Cora Meglioli, David Dale, Ning Dong, Paul-Ambroise Duquenne, Hady Elsahar, Hongyu Gong, Kevin Heffernan, John Hoffman, Christopher Klaiber, Pengwei Li, Daniel Licht, Jean Maillard, Alice Rakotoarison, Kaushik Ram Sadagopan, Guillaume Wenzek, Ethan Ye, Bapi Akula, Peng-Jen Chen, Naji El Hachem, Brian Ellis, Gabriel Mejia Gonzalez, Justin Haaheim, Prangthip Hansanti, Russ Howes, Bernie Huang, Min-Jae Hwang, Hirofumi Inaguma, Somya Jain, Elahe Kalbassi, Amanda Kallet, Ilia Kulikov, Janice Lam, Daniel Li, Xutai Ma, Ruslan Mavlyutov, Benjamin Peloquin, Mohamed Ramadan, Abinesh Ramakrishnan, Anna Sun, Kevin Tran, Tuan Tran, Igor Tufanov, Vish Vogeti, Carleigh Wood, Yilin Yang, Bokai Yu, Pierre Andrews, Can Balioglu, Marta R. Costa-jussà, Onur Celebi, Maha Elbayad, Cynthia Gao, Francisco Guzmán, Justine Kao, Ann Lee, Alexandre Mourachko, Juan Pino, Sravya Popuri, Christophe Ropers, Safiyyah Saleem, Holger Schwenk, Paden Tomasello, Changhan Wang, Jeff Wang, and Skyler Wang · 2023
Later among the works it cites.
Multilingual holistic bias: Extending descriptors and patterns to unveil demographic biases in languages at scale
Marta Costa-jussà, Pierre Andrews, Eric Smith, Prangthip Hansanti, Christophe Ropers, Elahe Kalbassi, Cynthia Gao, Daniel Licht, and Carleigh Wood · 2023
Later among the works it cites.
Toxicity in multilingual machine translation at scale
Marta Costa-jussà, Eric Smith, Christophe Ropers, Daniel Licht, Jean Maillard, Javier Ferrando, and Carlos Escolano · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Mojtaba Komeili, Kurt Shuster, and Jason Weston · 2022
Cited alongside, same era.
No language left behind: Scaling human-centered machine translation, 2022
NLLB Team, Marta R. Costa-jussà, James Cross, Onur Çelebi, Maha Elbayad, Kenneth Heafield, Kevin Heffernan, Elahe Kalbassi, Janice Lam, Daniel Licht, Jean Maillard, Anna Sun, Skyler Wang, Guillaume Wenzek, Al Youngblood, Bapi Akula, Loic Barrault, Gabriel Mejia Gonzalez, Prangthip Hansanti, John Hoffman, Semarley Jarrett, Kaushik Ram Sadagopan, Dirk Rowe, Shannon Spruit, Chau Tran, Pierre Andrews, Necip Fazil Ayan, Shruti Bhosale, Sergey Edunov, Angela Fan, Cynthia Gao, Vedanuj Goswami, Francisco Guzmán, Philipp Koehn, Alexandre Mourachko, Christophe Ropers, Safiyyah Saleem, Holger Schwenk, and Jeff Wang · 2022
Cited alongside, same era.
Augly: Data augmentations for robustness
Zoe Papakipos and Joanna Bitton · 2022
Cited alongside, same era.
Perturbation augmentation for fairer nlp
Rebecca Qian, Candace Ross, Jude Fernandes, Eric Smith, Douwe Kiela, and Adina Williams · 2022
Cited alongside, same era.
Investigating failures of automatic translationin the case of unambiguous gender
Adithya Renduchintala and Adina Williams · 2022
Cited alongside, same era.
“I’m sorry to hear that”: Finding new biases in language models with a holistic descriptor dataset
Eric Michael Smith, Melissa Hall, Melanie Kambadur, Eleonora Presani, and Adina Williams · 2022
Cited alongside, same era.
Benjamin Muller, Belen Alastruey, Prangthip Hansanti, Elahe Kalbassi, Christophe Ropers, Eric Smith, Adina Williams, Luke Zettlemoyer, Pierre Andrews, and Marta R. Costa-jussà · 2023
Later among the works it cites.
The unequal opportunities of large language models: Examining demographic biases in job recommendations by chatgpt and llama
Abel Salinas, Parth Shah, Yuzhong Huang, Robert McCormack, and Fred Morstatter · 2023
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models, 2023
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
Later among the works it cites.
Decodingtrust: A comprehensive assessment of trustworthiness in gpt models
Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, and Bo Li · 2023
Later among the works it cites.
Occgen: selection of real-world multilingual parallel data balanced in gender within occupations
Marta R. Costa-jussà, Christine Basta, Oriol Domingo, and Andre Niyongabo Rubungo · 2024
Closest in time.
In MuTox: Universal MUltilingual Audio-based TOXicity Dataset and Zero-shot Detector , 2024
Marta R. Costa-jussà, Mariano Coria Meglioli, Pierre Andrews, David Dale, Prangthip Hansanti, Elahe Kalbassi, Alex Mourachko, Christophe Ropers, and Carleigh Wood · 2024
Closest in time.
Trustworthy llms: a survey and guideline for evaluating large language models’ alignment, 2024
Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo, Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, and Hang Li · 2024
Closest in time.
Gender-specific machine translation with large language models, 2024
Eduardo Sánchez, Pierre Andrews, Pontus Stenetorp, Mikel Artetxe, and Marta R. Costa-jussà · 2024
Closest in time.