---
title: "Who cites Challenges in Automated Debiasing for Toxic…"
description: "77 papers of the Elamur Research library cite «Challenges in Automated Debiasing for Toxic Language Detection», found in their bibliographies; the most…"
canonical: "https://research.elamur.ai/free/en/papers/zhou-2021-challenges-automated-debiasing-toxic-language/cited-by/"
---
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# Who cites «Challenges in Automated Debiasing for Toxic Language Detection»

77 papers of our library cite it (of the 140,884 whose bibliographies we read) · 10 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/zhou-2021-challenges-automated-debiasing-toxic-language/)

1. [**On the Opportunities and Risks of Foundation Models**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,044 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-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. [**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/)
4. [**Having Beer after Prayer? Measuring Cultural Bias in Large Language Models**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 268 citations*](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/)
5. [**Challenges in Detoxifying Language Models**Johannes Welbl, Amelia Glaese, Jonathan Uesato, et al.*2021 · 206 citations*](https://md.research.elamur.ai/free/en/papers/welbl-2021-challenges-detoxifying-language-models/)
6. [**ProsocialDialog: A Prosocial Backbone for Conversational Agents**Hyunwoo Kim, Youngjae Yu, Liwei Jiang, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/kim-2022-prosocialdialog-prosocial-backbone-conversational-agents/)
7. [**SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents**Xuhui Zhou, Hao Zhu, Leena Mathur, et al.*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-sotopia-interactive-evaluation-social-intelligence/)
8. [**ToxicChat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User-AI Conversation**Zi Lin, Zihan Wang, Yongqi Tong, et al.*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-toxicchat-unveiling-hidden-challenges-toxicity/)
9. [**Multi-VALUE: A Framework for Cross-Dialectal English NLP**Caleb Ziems, William Held, Jingfeng Yang, et al.*2023 · 73 citations*](https://md.research.elamur.ai/free/en/papers/ziems-2023-multi-value-framework-cross-dialectal/)
10. [**DADA: Dialect Adaptation via Dynamic Aggregation of Linguistic Rules**Yanchen Liu, William Held, Diyi Yang*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-dada-dialect-adaptation-dynamic-aggregation/)

67 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/zhou-2021-challenges-automated-debiasing-toxic-language/) — Challenges in Automated Debiasing for Toxic Language Detection