---
title: "Who cites Red-Teaming Large Language — 92 citing papers"
description: "92 papers of the Elamur Research library cite «Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment»…"
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# Who cites «Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment»

92 papers of our library cite it (of the 149,439 whose bibliographies we read) · 28 with a page here, the most cited first · [← back to «Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment»](https://md.research.elamur.ai/free/en/papers/bhardwaj-2023-red-teaming-large-language-models/)

1. [**LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset arXiv:2309.11998**Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.*2023 · 242 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-lmsys-chat-1m-large-scale/)
2. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
3. [**Multilingual Jailbreak Challenges in Large Language Models arXiv:2310.06474**Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, et al.*2023 · 192 citations*](https://md.research.elamur.ai/free/en/papers/deng-2023-multilingual-jailbreak-challenges-large-language/)
4. **[SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-salad-bench-hierarchical-comprehensive-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lijun Li, Bowen Dong, Ruohui Wang, et al.*2024 · 119 citations*
5. **[R-Judge: Benchmarking Safety Risk Awareness for LLM Agents](https://md.research.elamur.ai/free/en/papers/yuan-2024-r-judge-benchmarking-safety-risk/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tongxin Yuan, Zhiwei He, Lingzhong Dong, et al.*2024 · 106 citations*
6. [**Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models arXiv:2310.02949**Xianjun Yang, Xiao Wang, Qi Zhang, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-shadow-alignment-ease-subverting-safely/)
7. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
8. **[Aligner: Efficient Alignment by Learning to Correct](https://md.research.elamur.ai/free/en/papers/ji-2024-aligner-efficient-alignment-learning-correct/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaming Ji, Boyuan Chen, Hantao Lou, et al.*2024 · 69 citations*
9. **[Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task Arithmetic](https://md.research.elamur.ai/free/en/papers/bhardwaj-2024-language-models-are-homer-simpson/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rishabh Bhardwaj, Duc Anh Do, Soujanya Poria*2024 · 59 citations*
10. **[AEGIS2.0: A Diverse AI Safety Dataset and Risks Taxonomy for Alignment of LLM Guardrails](https://md.research.elamur.ai/free/en/papers/ghosh-2025-aegis2-0-diverse-ai-safety/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Shaona Ghosh, Prasoon Varshney, Makesh Narsimhan Sreedhar, et al.*2025 · 53 citations*
11. [**Introducing v0.5 of the AI Safety Benchmark from MLCommons arXiv:2404.12241**Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2024-introducing-v0-5-ai-safety/)
12. [**SciKnowEval: Evaluating Multi-level Scientific Knowledge of Large Language Models arXiv:2406.09098**Kehua Feng, Xinyi Shen, Weijie Wang, et al.*2024 · 36 citations*](https://md.research.elamur.ai/free/en/papers/feng-2024-sciknoweval-evaluating-multi-level-scientific/)
13. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
14. **[AraTrust: An Evaluation of Trustworthiness for LLMs in Arabic](https://md.research.elamur.ai/free/en/papers/alghamdi-2025-aratrust-evaluation-trustworthiness-llms-arabic/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Emad A. Alghamdi, Reem I. Masoud, Deema Alnuhait, et al.*2025 · 26 citations*
15. **[Arabic Dataset for LLM Safeguard Evaluation](https://md.research.elamur.ai/free/en/papers/ashraf-2025-arabic-dataset-llm-safeguard-evaluation/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yasser Ashraf, Yuxia Wang, Bin Gu, et al.*2025 · 22 citations*
16. **[Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs](https://md.research.elamur.ai/free/en/papers/xia-2025-beyond-chain-thought-survey-chain/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yu Xia, Rui Wang, Xu Liu, et al.*2025 · 19 citations*
17. **[Shaping the Safety Boundaries: Understanding and Defending Against Jailbreaks in Large Language Models](https://md.research.elamur.ai/free/en/papers/gao-2025-shaping-safety-boundaries-understanding-defending/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lang Gao, Jiahui Geng, Xiangliang Zhang, et al.*2025 · 19 citations*
18. **[MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teaming](https://md.research.elamur.ai/free/en/papers/guo-2025-mtsa-multi-turn-safety-alignment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiyang Guo, Jing Li, Wenya Wang, et al.*2025 · 14 citations*
19. **[Automated Progressive Red Teaming](https://md.research.elamur.ai/free/en/papers/jiang-2025-automated-progressive-red-teaming/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Bojian Jiang, Yi Jing, Tong Wu, et al.*2025 · 10 citations*
20. **[HAUNTATTACK: When Attack Follows Reasoning as a Shadow](https://md.research.elamur.ai/free/en/papers/ma-2026-hauntattack-when-attack-follows-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingyuan Ma, Rui Li, Zheng Li, et al.*2026 · 3 citations*
21. **[Activation-Guided Local Editing for Jailbreaking Attacks](https://md.research.elamur.ai/free/en/papers/wang-2026-activation-guided-local-editing-jailbreaking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiecong Wang, Haoran Li, Hao Peng, et al.*2026 · 1 citation*
22. **[AMALIA: A Fully Open Large Language Model for European Portuguese](https://md.research.elamur.ai/free/en/papers/simplicio-2026-amalia-fully-open-large-language/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Afonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos, et al.*2026 · 1 citation*
23. **[Mind the Language Gap: Assessing LLM Safety in Italian](https://md.research.elamur.ai/free/en/papers/marafatto-2026-mind-language-gap-assessing-llm/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Elena Marafatto, Roberto Navigli*2026*
24. [**SalamahBench: Dialect and Category Level Safety Evaluation of Arabic Language Models arXiv:2603.04410**Omar Abdelnasser, Fatemah Alharbi, Khaled Khasawneh, et al.*2026*](https://md.research.elamur.ai/free/en/papers/abdelnasser-2026-salamahbench-dialect-category-level-safety/)
25. **[Simple Role Assignment is Extraordinarily Effective for Safety Alignment](https://md.research.elamur.ai/free/en/papers/ziheng-2026-simple-role-assignment-is-extraordinarily/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhou Ziheng, Jiakun Ding, Zhaowei Zhang, et al.*2026*
26. **[StealthGraph: Exposing Domain-Specific Risks in LLMs through Knowledge-Graph-Guided Harmful Prompt Generation](https://md.research.elamur.ai/free/en/papers/zheng-2026-stealthgraph-exposing-domain-specific-risks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huawei Zheng, Xinqi Jiang, Sen Yang, et al.*2026*
27. **[When Prompt Optimization Becomes Jailbreaking: Adaptive Red-Teaming of Large Language Models](https://md.research.elamur.ai/free/en/papers/shamsi-2026-when-prompt-optimization-becomes-jailbreaking/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zafir Shamsi, Nikhil Chekuru, Zachary Guzman, et al.*2026*
28. **[You Only Need One Single Token to Refine Safety Alignment](https://md.research.elamur.ai/free/en/papers/yu-2026-you-only-need-one-single/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenqian Yu, Shuo Chen, Zhijiang Li, et al.*2026*

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

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