--- title: "Who cites A Survey of Safety and — 41 citing papers" description: "41 papers of the Elamur Research library cite «A Survey of Safety and Trustworthiness of Large Language Models through the Lens of…" canonical: "https://research.elamur.ai/free/en/papers/huang-2023-survey-safety-trustworthiness-large-language/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/huang-2023-survey-safety-trustworthiness-large-language/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [A Survey of Safety and Trustworthiness of Large…](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-safety-trustworthiness-large-language/) / cited by # Who cites «A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation» 41 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · [← back to «A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation»](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-safety-trustworthiness-large-language/) 1. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations* 2. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/) 3. **[Combating Misinformation in the Age of LLMs: Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/chen-2023-combating-misinformation-age-llms-opportunities/) [AI Magazine](https://md.research.elamur.ai/free/en/venues/ai-magazine/)**Canyu Chen, Kai Shu*2023 · 214 citations* 4. **[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* 5. **[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* 6. [**Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs arXiv:2507.09477**Yangning Li, Weizhi Zhang, Yuyao Yang, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-towards-agentic-rag-deep-reasoning/) 7. **[Safety Alignment via Constrained Knowledge Unlearning](https://md.research.elamur.ai/free/en/papers/shi-2025-safety-alignment-constrained-knowledge-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zesheng Shi, Yucheng Zhou, Jing Li, et al.*2025 · 13 citations* 8. **[IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation](https://md.research.elamur.ai/free/en/papers/wen-2026-if-critic-fine-grained-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bosi Wen, Yilin Niu, Cunxiang Wang, et al.*2026 · 1 citation* 9. **[IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation](https://md.research.elamur.ai/free/en/papers/wen-2026-if-rewardbench-benchmarking-judge-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bosi Wen, Yilin Niu, Cunxiang Wang, et al.*2026 · 1 citation* 10. **[Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/song-2026-hard-read-easy-jailbreak-how/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhixue Song, Boyan Han, Yiwei Wang, et al.*2026* 31 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-safety-trustworthiness-large-language/) — A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation