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Data annotation, the practice of assigning descriptive labels to raw data, is pivotal in optimizing the performance of machine learning models.
Explaining odds ratios
Magdalena Szumilas · 2010
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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 T Kalai · 2016
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The trouble with bias
Kate Crawford · 2017
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A survey on hate speech detection using natural language processing
Anna Schmidt and Michael Wiegand · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Measuring and mitigating unintended bias in text classification
Lucas Dixon, John Li, Jeffrey Sorensen, Nithum Thain, and Lucy Vasserman · 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
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Identifying and reducing gender bias in word-level language models
Shikha Bordia and Samuel R Bowman · 2019
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Queens are powerful too: Mitigating gender bias in dialogue generation
Emily Dinan, Angela Fan, Adina Williams, Jack Urbanek, Douwe Kiela, and Jason Weston · 2019
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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
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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
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Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A Smith · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
Cited alongside, same era.
Towards controllable biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng · 2020
Cited alongside, same era.
On measures of biases and harms in nlp
Sunipa Dev, Emily Sheng, Jieyu Zhao, Aubrie Amstutz, Jiao Sun, Yu Hou, Mattie Sanseverino, Jiin Kim, Akihiro Nishi, Nanyun Peng, et al · 2021
Cited alongside, same era.
Bold: Dataset and metrics for measuring biases in open-ended language generation
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
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Ethos: a multi-label hate speech detection dataset
Ioannis Mollas, Zoe Chrysopoulou, Stamatis Karlos, and Grigorios Tsoumakas · 2022
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Is GPT-3 a good data annotator?
Bosheng Ding, Chengwei Qin, Linlin Liu, Yew Ken Chia, Boyang Li, Shafiq Joty, and Lidong Bing · 2023
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Chatgpt outperforms crowd workers for text-annotation tasks
Fabrizio Gilardi, Meysam Alizadeh, and Maël Kubli · 2023
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Annollm: Making large language models to be better crowdsourced annotators
Xingwei He, Zhenghao Lin, Yeyun Gong, Alex Jin, Hang Zhang, Chen Lin, Jian Jiao, Siu Ming Yiu, Nan Duan, Weizhu Chen, et al · 2023
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Jwala Dhamala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, and Rahul Gupta · 2021
Cited alongside, same era.
Dexperts: Decoding-time controlled text generation with experts and anti-experts
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A Smith, and Yejin Choi · 2021
Cited alongside, same era.
Men are elected, women are married: Events gender bias on wikipedia
Jiao Sun and Nanyun Peng · 2021
Cited alongside, same era.
Want to reduce labeling cost? GPT-3 can help
Shuohang Wang, Yang Liu, Yichong Xu, Chenguang Zhu, and Michael Zeng · 2021
Cited alongside, same era.
Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta, Varun Kumar, Jwala Dhamala, and Aram Galstyan · 2022
Cited alongside, same era.
Sehc: A benchmark setup to identify online hate speech in english
Soumitra Ghosh, Asif Ekbal, Pushpak Bhattacharyya, Tista Saha, Alka Kumar, and Shikha Srivastava · 2022
Cited alongside, same era.
Later among the works it cites.
Chatgpt: Beginning of an end of manual linguistic data annotation? use case of automatic genre identification, 2023
Taja Kuzman, Igor Mozetič, and Nikola Ljubešić · 2023
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Can chatgpt reproduce human-generated labels? a study of social computing tasks
Yiming Zhu, Peixian Zhang, Ehsan-Ul Haq, Pan Hui, and Gareth Tyson · 2023
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Amit Das, Mostafa Rahgouy, Dongji Feng, Zheng Zhang, Tathagata Bhattacharya, Nilanjana Raychawdhary, Mary Sandage, Lauramarie Pope, Gerry Dozier, and Cheryl Seals · 2024
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Large language models for data annotation: A survey
Zhen Tan, Dawei Li, Song Wang, Alimohammad Beigi, Bohan Jiang, Amrita Bhattacharjee, Mansooreh Karami, Jundong Li, Lu Cheng, and Huan Liu · 2024
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Can large language models transform computational social science?
Caleb Ziems, William Held, Omar Shaikh, Jiaao Chen, Zhehao Zhang, and Diyi Yang · 2024
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