---
title: "Who cites Aida Mostafazadeh Davani"
description: "336 papers of the Elamur Research library cite the works of Aida Mostafazadeh Davani, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/aida-mostafazadeh-davani/cited-by/"
---
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# 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](https://md.research.elamur.ai/free/en/authors/aida-mostafazadeh-davani/)

1. [**Bias and Fairness in Large Language Models: A Survey**Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.*2023 · 1,072 citations*](https://md.research.elamur.ai/free/en/papers/gallegos-2023-bias-fairness-large-language-models/)
2. [**ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection**Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, et al.*2022 · 571 citations*](https://md.research.elamur.ai/free/en/papers/hartvigsen-2022-toxigen-large-scale-machine-generated/)
3. [**Whose Opinions Do Language Models Reflect?**Shibani Santurkar, Esin Durmus, Faisal Ladhak, et al.*2023 · 390 citations*](https://md.research.elamur.ai/free/en/papers/santurkar-2023-whose-opinions-language-models-reflect/)
4. [**Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection**Maarten Sap, Swabha Swayamdipta, Laura Vianna, et al.*2022 · 364 citations*](https://md.research.elamur.ai/free/en/papers/sap-2022-annotators-attitudes-how-annotator-beliefs/)
5. [**The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation**Barbara Plank*2022 · 364 citations*](https://md.research.elamur.ai/free/en/papers/plank-2022-problem-human-label-variation-ground/)
6. [**Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection**Bertie Vidgen, Tristan Thrush, Zeerak Waseem, et al.*2021 · 320 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2021-learning-worst-dynamically-generated-datasets/)
7. [**From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models**Shangbin Feng, Chan Young Park, Yuhan Liu, et al.*2023 · 305 citations*](https://md.research.elamur.ai/free/en/papers/feng-2023-pretraining-data-language-models-downstream/)
8. [**Challenges and Applications of Large Language Models**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
9. [**Challenges and Strategies in Cross-Cultural NLP**Daniel Hershcovich, Stella Frank, Heather Lent, et al.*2022 · 290 citations*](https://md.research.elamur.ai/free/en/papers/hershcovich-2022-challenges-strategies-cross-cultural-nlp/)
10. [**Towards Measuring the Representation of Subjective Global Opinions in Language Models**Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.*2023 · 262 citations*](https://md.research.elamur.ai/free/en/papers/durmus-2023-towards-measuring-representation-subjective-global/)
11. [**A Holistic Approach to Undesired Content Detection in the Real World**Todor Markov, Chong Zhang, Sandhini Agarwal, et al.*2022 · 254 citations*](https://md.research.elamur.ai/free/en/papers/markov-2022-holistic-approach-undesired-content-detection/)
12. [**XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models**Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.*2023 · 227 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2023-xstest-test-suite-identifying-exaggerated/)
13. [**Two Contrasting Data Annotation Paradigms for Subjective NLP Tasks**Paul Röttger, Bertie Vidgen, Dirk Hovy, et al.*2022 · 219 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2022-two-contrasting-data-annotation-paradigms/)
14. [**HateCheck: Functional Tests for Hate Speech Detection Models**Paul Röttger, Bertie Vidgen, Dong Nguyen, et al.*2021 · 202 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2021-hatecheck-functional-tests-hate-speech/)
15. [**HONEST: Measuring Hurtful Sentence Completion in Language Models**Debora Nozza, Federico Bianchi, Dirk Hovy*2021 · 190 citations*](https://md.research.elamur.ai/free/en/papers/nozza-2021-honest-measuring-hurtful-sentence-completion/)
16. [**SemEval-2023 Task 10: Explainable Detection of Online Sexism**Hannah Kirk, Wenjie Yin, Bertie Vidgen, et al.*2023 · 185 citations*](https://md.research.elamur.ai/free/en/papers/kirk-2023-semeval-2023-task-10-explainable/)
17. [**AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages**Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele, et al.*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/muhammad-2023-afrisenti-twitter-sentiment-analysis-benchmark/)
18. [**NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis**Shamsuddeen Hassan Muhammad, David Ifeoluwa Adelani, Sebastian Ruder, et al.*2022 · 127 citations*](https://md.research.elamur.ai/free/en/papers/muhammad-2022-naijasenti-nigerian-twitter-sentiment-corpus/)
19. [**Investigating Reasons for Disagreement in Natural Language Inference**Nan-Jiang Jiang, Marie-Catherine de Marneffe*2022 · 104 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-investigating-reasons-disagreement-natural-language/)
20. [**Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/)
21. [**VariErr NLI: Separating Annotation Error from Human Label Variation**Leon Weber-Genzel, Siyao Peng, Marie-Catherine De Marneffe, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/genzel-2024-varierr-nli-separating-annotation-error/)
22. [**EPIC: Multi-Perspective Annotation of a Corpus of Irony**Simona Frenda, Alessandro Pedrani, Valerio Basile, et al.*2023 · 41 citations*](https://md.research.elamur.ai/free/en/papers/frenda-2023-epic-multi-perspective-annotation-corpus/)
23. [**MultiPICo: Multilingual Perspectivist Irony Corpus**Silvia Casola, Simona Frenda, Soda Marem Lo, et al.*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/casola-2024-multipico-multilingual-perspectivist-irony-corpus/)
24. [**The Moral Foundations Reddit Corpus**Jackson P. Trager, Alireza S. Ziabari, Elnaz Rahmati, et al.*2026 · 22 citations*](https://md.research.elamur.ai/free/en/papers/trager-2026-moral-foundations-reddit-corpus/)
25. [**Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design**Valentina Pyatkin, Frances Yung, Merel C. J. Scholman, et al.*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/pyatkin-2023-design-choices-crowdsourcing-implicit-discourse/)
26. [**A Corpus for Sentence-Level Subjectivity Detection on English News Articles**Francesco Antici, Federico Ruggeri, Andrea Galassi, et al.*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/antici-2024-corpus-sentence-level-subjectivity-detection/)
27. [**Can LLMs Evaluate What They Cannot Annotate? Revisiting LLM Reliability in Hate Speech Detection**Paloma Piot, David Otero, Patricia Martin-Rodilla, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/piot-2026-can-llms-evaluate-what-they/)
28. [**LLMs as Annotators: Evaluating Model–Human Alignment in Detecting Contentious Language in Historical Corpora**Yahui Zhao, Clemencia Siro, Laura Hollink*2026*](https://md.research.elamur.ai/free/en/papers/zhao-2026-llms-as-annotators-evaluating-model/)

308 more citing papers of our library have no page here yet.

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