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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts
Yue Guo, Yi Yang, Ahmed Abbasi
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022)
Open Access | Times Cited: 81

Showing 26-50 of 81 citing articles:

Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases
Yingji Li, Mengnan Du, Xin Wang, et al.
(2023)
Open Access | Times Cited: 7
Causal-Debias: Unifying Debiasing in Pretrained Language Models and Fine-tuning via Causal Invariant Learning
Fan Zhou, Yuzhou Mao, Yu Liu, et al.
(2023), pp. 4227-4241
Open Access | Times Cited: 7
Perils and Opportunities in Using Large Language Models in Psychological Research
Suhaib Abdurahman, Mohammad Atari, Farzan Karimi-Malekabadi, et al.
(2023)
Open Access | Times Cited: 7
Perils and Opportunities in Using Large Language Models in Psychological Research
Suhaib Abdurahman, Mohammad Atari, Farzan Karimi-Malekabadi, et al.
(2023)
Open Access | Times Cited: 7
MABEL: Attenuating Gender Bias using Textual Entailment Data
Jacqueline He, Mengzhou Xia, Christiane Fellbaum, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022), pp. 9681-9702
Open Access | Times Cited: 11
Biases Mitigation and Expressiveness Preservation in Language Models: A Comprehensive Pipeline (Student Abstract)
Yu Liu, Ludie Guo, Ping Kuang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 21, pp. 23701-23702
Open Access | Times Cited: 2
Debiasing large language models: research opportunities*
Vithya Yogarajan, Gillian Dobbie, Te Taka Keegan
Journal of the Royal Society of New Zealand (2024) Vol. 55, Iss. 2, pp. 372-395
Open Access | Times Cited: 2
Navigate Beyond Shortcuts: Debiased Learning through the Lens of Neural Collapse
Yining Wang, Junjie Sun, Chenyue Wang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 35, pp. 12322-12331
Closed Access | Times Cited: 2
Extractive Explanations for Interpretable Text Ranking
Jurek Leonhardt, Koustav Rudra, Avishek Anand
ACM transactions on office information systems (2022) Vol. 41, Iss. 4, pp. 1-31
Open Access | Times Cited: 9
Learning Debiased Representations via Conditional Attribute Interpolation
Yikai Zhang, Qiwei Wang, De‐Chuan Zhan, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023) Vol. 45, pp. 7599-7608
Closed Access | Times Cited: 5
Data Science for Social Good
Ahmed Abbasi, Roger H.L. Chiang, Jennifer Xu
Journal of the Association for Information Systems (2023) Vol. 24, Iss. 6, pp. 1439-1458
Open Access | Times Cited: 5
Bridging Fairness and Environmental Sustainability in Natural Language Processing
Marius Hessenthaler, Emma Strubell, Dirk Hovy, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022), pp. 7817-7836
Open Access | Times Cited: 8
Learning to Generate Equitable Text in Dialogue from Biased Training Data
Anthony Sicilia, Malihe Alikhani
(2023)
Open Access | Times Cited: 4
Evaluating and mitigating unfairness in multimodal remote mental health assessments
Zifan Jiang, Salman Seyedi, Emily Griner, et al.
PLOS Digital Health (2024) Vol. 3, Iss. 7, pp. e0000413-e0000413
Open Access | Times Cited: 1
Locating and Mitigating Gender Bias in Large Language Models
Y. Cai, Ding Cao, Rongxi Guo, et al.
Lecture notes in computer science (2024), pp. 471-482
Closed Access | Times Cited: 1
Causal keyword driven reliable text classification with large language model feedback
Rui Song, Yingji Li, Mingjie Tian, et al.
Information Processing & Management (2024) Vol. 62, Iss. 2, pp. 103964-103964
Closed Access | Times Cited: 1
Speciesism in natural language processing research
Masashi Takeshita, Rafał Rzepka
AI and Ethics (2024)
Open Access | Times Cited: 1
How do different tokenizers perform on downstream tasks in scriptio continua languages?: A case study in Japanese
Takuro Fujii, Koki Shibata, Atsuki Yamaguchi, et al.
(2023), pp. 39-49
Open Access | Times Cited: 3
Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP)
Idris Akinade, Jesujoba O. Alabi, David Ifeoluwa Adelani, et al.
(2023)
Open Access | Times Cited: 3
Disparities in seizure outcomes revealed by large language models
Kevin Xie, William K.S. Ojemann, Ryan S. Gallagher, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 3
Compensatory Debiasing For Gender Imbalances In Language Models
Tae-Jin Woo, Woo-Jeoung Nam, Yeong-Joon Ju, et al.
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2023), pp. 1-5
Closed Access | Times Cited: 2
Reducing Sentiment Bias in Pre-trained Sentiment Classification via Adaptive Gumbel Attack
Jiachen Tian, Shizhan Chen, Xiaowang Zhang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 11, pp. 13646-13654
Open Access | Times Cited: 2
Mixup-based Unified Framework to Overcome Gender Bias Resurgence
Yu Liu, Yuzhou Mao, Jin Wu, et al.
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2023), pp. 1755-1759
Closed Access | Times Cited: 2
How does the task complexity of masked pretraining objectives affect downstream performance?
Atsuki Yamaguchi, Hiroaki Ozaki, Terufumi Morishita, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2023), pp. 10527-10537
Open Access | Times Cited: 2
Towards Alleviating the Object Bias in Prompt Tuning-based Factual Knowledge Extraction
Yuhang Wang, Dongyuan Lu, Chao Kong, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2023), pp. 4420-4432
Open Access | Times Cited: 2

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