--- title: "Who cites Foundational Challenges in — 70 citing papers" description: "70 papers of the Elamur Research library cite «Foundational Challenges in Assuring Alignment and Safety of Large Language Models»…" canonical: "https://research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Foundational Challenges in Assuring Alignment and…](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/) / cited by # Who cites «Foundational Challenges in Assuring Alignment and Safety of Large Language Models» 70 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← back to «Foundational Challenges in Assuring Alignment and Safety of Large Language Models»](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/) 1. **[WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs](https://md.research.elamur.ai/free/en/papers/han-2024-wildguard-open-one-stop-moderation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Seungju Han, Kavel Rao, Allyson Ettinger, et al.*2024 · 165 citations* 2. [**Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations arXiv:2310.06387**Zeming Wei, Yifei Wang, Ang Li, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbreak-guard-aligned-language-models/) 3. [**Can LLM-Generated Misinformation Be Detected? arXiv:2309.13788**Canyu Chen, Kai Shu*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-llm-generated-misinformation-detected/) 4. **[WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-wildteaming-scale-wild-jailbreaks-adversarially/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Liwei Jiang, Kavel Rao, Seungju Han, et al.*2024 · 92 citations* 5. [**OR-Bench: An Over-Refusal Benchmark for Large Language Models arXiv:2405.20947**Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/cui-2024-bench-over-refusal-benchmark-large/) 6. **[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* 7. **[The Art of Saying No: Contextual Noncompliance in Language Models](https://md.research.elamur.ai/free/en/papers/brahman-2024-art-saying-no-contextual-noncompliance/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.*2024 · 56 citations* 8. [**Observational Scaling Laws and the Predictability of Language Model Performance arXiv:2405.10938**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/) 9. **[The State of Multilingual LLM Safety Research: From Measuring The Language Gap To Mitigating It](https://md.research.elamur.ai/free/en/papers/yong-2025-state-multilingual-llm-safety-research/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zheng Xin Yong, Beyza Ermis, Marzieh Fadaee, et al.*2025 · 25 citations* 10. [**Language Model Alignment in Multilingual Trolley Problems arXiv:2407.02273**Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-language-model-alignment-multilingual-trolley/) 11. **[Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms](https://md.research.elamur.ai/free/en/papers/wang-2025-beyond-prompt-engineering-robust-behavior/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengru Wang, Ziwen Xu, Shengyu Mao, et al.*2025 · 14 citations* 12. [**Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models arXiv:2407.15645**Joy He-Yueya, Wanjing Anya Ma, Kanishk Gandhi, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/he-yueya-2024-psychometric-alignment-capturing-human-knowledge/) 13. **[False Sense of Security: Why Probing-based Malicious Input Detection Fails to Generalize](https://md.research.elamur.ai/free/en/papers/wang-2026-false-sense-security-why-probing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Wang, Zeming Wei, Qin Liu, et al.*2026 · 5 citations* 14. **[HiddenGuard: Fine-Grained Safe Generation with Specialized Representation Router](https://md.research.elamur.ai/free/en/papers/mei-2026-hiddenguard-fine-grained-safe-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 4 citations* 15. **[A Simple and Efficient Learning-Style Prompting for LLM Jailbreaking](https://md.research.elamur.ai/free/en/papers/luo-2026-simple-efficient-learning-style-prompting/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Luo, Yue Wang, Zefeng He, et al.*2026* 16. **[Calibrating Inference Time Alignment with Sequence-level Risk Accumulation](https://md.research.elamur.ai/free/en/papers/tan-2026-calibrating-inference-time-alignment-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shanwen Tan, Ziyang Dong, Wei Ju, et al.*2026* 17. **[Deactivating Refusal Triggers: Understanding and Mitigating Overrefusal in Safety Alignment](https://md.research.elamur.ai/free/en/papers/xue-2026-deactivating-refusal-triggers-understanding-mitigating/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Zhiyu Xue, Zimo Qi, Guangliang Liu, et al.*2026* 18. **[How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities](https://md.research.elamur.ai/free/en/papers/xu-2026-how-controllable-are-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwen Xu, Kewei Xu, Haoming Xu, et al.*2026* 52 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/) — Foundational Challenges in Assuring Alignment and Safety of Large Language Models