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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:

ValNorm Quantifies Semantics to Reveal Consistent Valence Biases Across Languages and Over Centuries
Autumn Toney, Aylin Caliskan
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
Open Access | Times Cited: 15

Showing 15 citing articles:

Safeguarding human values: rethinking US law for generative AI’s societal impacts
Inyoung Cheong, Aylin Caliskan, Tadayoshi Kohno
AI and Ethics (2024)
Open Access | Times Cited: 11
Awe fosters positive attitudes toward solitude
Yige Yin, Wenying Yuan, Chenxiao Hao, et al.
Nature Mental Health (2024) Vol. 2, Iss. 6, pp. 717-727
Open Access | Times Cited: 7
Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models
Robert E. Wolfe, Aylin Caliskan
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
Open Access | Times Cited: 27
Evaluating Biased Attitude Associations of Language Models in an Intersectional Context
Shiva Omrani Sabbaghi, Robert Wolfe, Aylin Caliskan
(2023), pp. 542-553
Open Access | Times Cited: 9
More utilitarian and less rational? Social change and two types of individualism over the last 40 years in China

Acta Psychologica Sinica (2024) Vol. 56, Iss. 7, pp. 911-911
Open Access | Times Cited: 2
VAST: The Valence-Assessing Semantics Test for Contextualizing Language Models
Robert E. Wolfe, Aylin Caliskan
Proceedings of the AAAI Conference on Artificial Intelligence (2022) Vol. 36, Iss. 10, pp. 11477-11485
Open Access | Times Cited: 11
Reproducibility in Computational Linguistics: Is Source Code Enough?
Mohammad Arvan, Luís Pina, Natalie Parde
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022), pp. 2350-2361
Open Access | Times Cited: 10
Predicting implicit attitudes with natural language data
Sudeep Bhatia, Lukasz Walasek
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 25
Open Access | Times Cited: 4
Contrastive Visual Semantic Pretraining Magnifies the Semantics of Natural Language Representations
Robert E. Wolfe, Aylin Caliskan
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022), pp. 3050-3061
Open Access | Times Cited: 4
Measuring Gender Bias in Word Embeddings of Gendered Languages Requires Disentangling Grammatical Gender Signals
Shiva Omrani Sabbaghi, Aylin Caliskan
(2022), pp. 518-531
Open Access | Times Cited: 3
Regional Bias in Monolingual English Language Models
Jiachen Lyu, Katharina Dost, Yun Sing Koh, et al.
Research Square (Research Square) (2024)
Open Access
Sustainability in Leadership: The Implicit Associations of the First-Person Pronouns and Leadership Effectiveness Based on Word Embedding Association Test
Qu Yao, Yingjie Zheng, Jianhang Chen
Sustainability (2024) Vol. 16, Iss. 15, pp. 6403-6403
Open Access
The (Undesired) Attenuation of Human Biases by Multilinguality
Cristina España-Bonet, Alberto Barrón‐Cedeño
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022), pp. 2056-2077
Open Access | Times Cited: 2
Pre-trained Speech Processing Models Contain Human-Like Biases that Propagate to Speech Emotion Recognition
Isaac Slaughter, Craig S. Greenberg, Reva Schwartz, et al.
(2023), pp. 8967-8989
Open Access
Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models
Robert E. Wolfe, Aylin Caliskan
Empirical Methods in Natural Language Processing (2021), pp. 518-532
Closed Access
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