🧑‍🔬 Who cites Aida Mostafazadeh Davani

404 citations of their works from 336 papers of our library (of the 140,884 whose bibliographies we read) · 28 with a page here, the most cited first · ← Aida Mostafazadeh Davani

1. Bias and Fairness in Large Language Models: A SurveyIsabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.2023 · 1,072 citations
2. ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech DetectionThomas Hartvigsen, Saadia Gabriel, Hamid Palangi, et al.2022 · 571 citations
3. Whose Opinions Do Language Models Reflect?Shibani Santurkar, Esin Durmus, Faisal Ladhak, et al.2023 · 390 citations
4. Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language DetectionMaarten Sap, Swabha Swayamdipta, Laura Vianna, et al.2022 · 364 citations
5. The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and EvaluationBarbara Plank2022 · 364 citations
6. Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate DetectionBertie Vidgen, Tristan Thrush, Zeerak Waseem, et al.2021 · 320 citations
7. From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP ModelsShangbin Feng, Chan Young Park, Yuhan Liu, et al.2023 · 305 citations
8. Challenges and Applications of Large Language ModelsJean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 300 citations
9. Challenges and Strategies in Cross-Cultural NLPDaniel Hershcovich, Stella Frank, Heather Lent, et al.2022 · 290 citations
10. Towards Measuring the Representation of Subjective Global Opinions in Language ModelsEsin Durmus, Karina Nguyen, Thomas I. Liao, et al.2023 · 262 citations
11. A Holistic Approach to Undesired Content Detection in the Real WorldTodor Markov, Chong Zhang, Sandhini Agarwal, et al.2022 · 254 citations
12. XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language ModelsPaul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.2023 · 227 citations
13. Two Contrasting Data Annotation Paradigms for Subjective NLP TasksPaul Röttger, Bertie Vidgen, Dirk Hovy, et al.2022 · 219 citations
14. HateCheck: Functional Tests for Hate Speech Detection ModelsPaul Röttger, Bertie Vidgen, Dong Nguyen, et al.2021 · 202 citations
15. HONEST: Measuring Hurtful Sentence Completion in Language ModelsDebora Nozza, Federico Bianchi, Dirk Hovy2021 · 190 citations
16. SemEval-2023 Task 10: Explainable Detection of Online SexismHannah Kirk, Wenjie Yin, Bertie Vidgen, et al.2023 · 185 citations
17. AfriSenti: A Twitter Sentiment Analysis Benchmark for African LanguagesShamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele, et al.2023 · 143 citations
18. NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment AnalysisShamsuddeen Hassan Muhammad, David Ifeoluwa Adelani, Sebastian Ruder, et al.2022 · 127 citations
19. Investigating Reasons for Disagreement in Natural Language InferenceNan-Jiang Jiang, Marie-Catherine de Marneffe2022 · 104 citations
20. Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language GenerationPatrick Fernandes, Aman Madaan, Emmy Liu, et al.2023 · 84 citations
21. VariErr NLI: Separating Annotation Error from Human Label VariationLeon Weber-Genzel, Siyao Peng, Marie-Catherine De Marneffe, et al.2024 · 51 citations
22. EPIC: Multi-Perspective Annotation of a Corpus of IronySimona Frenda, Alessandro Pedrani, Valerio Basile, et al.2023 · 41 citations
23. MultiPICo: Multilingual Perspectivist Irony CorpusSilvia Casola, Simona Frenda, Soda Marem Lo, et al.2024 · 28 citations
24. The Moral Foundations Reddit CorpusJackson P. Trager, Alireza S. Ziabari, Elnaz Rahmati, et al.2026 · 22 citations
25. Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task DesignValentina Pyatkin, Frances Yung, Merel C. J. Scholman, et al.2023 · 19 citations
26. A Corpus for Sentence-Level Subjectivity Detection on English News ArticlesFrancesco Antici, Federico Ruggeri, Andrea Galassi, et al.2024 · 10 citations
27. Can LLMs Evaluate What They Cannot Annotate? Revisiting LLM Reliability in Hate Speech DetectionPaloma Piot, David Otero, Patricia Martin-Rodilla, et al.2026 · 5 citations
28. LLMs as Annotators: Evaluating Model–Human Alignment in Detecting Contentious Language in Historical CorporaYahui Zhao, Clemencia Siro, Laura Hollink2026

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