---
title: "Who cites Defending Against — 61 citing papers"
description: "61 papers of the Elamur Research library cite «Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/cao-2024-defending-against-alignment-breaking-attacks/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/cao-2024-defending-against-alignment-breaking-attacks/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Defending Against Alignment-Breaking Attacks via…](https://md.research.elamur.ai/free/en/papers/cao-2024-defending-against-alignment-breaking-attacks/) / cited by

# Who cites «Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM»

61 papers of our library cite it (of the 141,840 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM»](https://md.research.elamur.ai/free/en/papers/cao-2024-defending-against-alignment-breaking-attacks/)

1. [**A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly arXiv:2312.02003**Yifan Yao, Jinhao Duan, Kaidi Xu, et al.*2023 · 1,182 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-survey-large-language-model-llm/)
2. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
3. **[How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs](https://md.research.elamur.ai/free/en/papers/zeng-2024-how-johnny-can-persuade-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Zeng, Hongpeng Lin, Jingwen Zhang, et al.*2024 · 201 citations*
4. **[SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding](https://md.research.elamur.ai/free/en/papers/xu-2024-safedecoding-defending-against-jailbreak-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 126 citations*
5. [**Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations arXiv:2310.06387**Zeming Wei, Yifei Wang, Ang Li, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbreak-guard-aligned-language-models/)
6. **[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 · 114 citations*
7. **[Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization](https://md.research.elamur.ai/free/en/papers/zhang-2024-defending-large-language-models-against/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhexin Zhang, Junxiao Yang, Pei Ke, et al.*2024 · 112 citations*
8. **[Detoxifying Large Language Models via Knowledge Editing](https://md.research.elamur.ai/free/en/papers/wang-2024-detoxifying-large-language-models-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengru Wang, Ningyu Zhang, Ziwen Xu, et al.*2024 · 84 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/cao-2024-defending-against-alignment-breaking-attacks/) — Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM