--- title: "Who cites Hard Prompts Made Easy: — 81 citing papers" description: "81 papers of the Elamur Research library cite «Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and…" canonical: "https://research.elamur.ai/free/en/papers/wen-2023-hard-prompts-made-easy-gradient/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wen-2023-hard-prompts-made-easy-gradient/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Hard Prompts Made Easy: Gradient-Based Discrete…](https://md.research.elamur.ai/free/en/papers/wen-2023-hard-prompts-made-easy-gradient/) / cited by # Who cites «Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery» 81 papers of our library cite it (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · [← back to «Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery»](https://md.research.elamur.ai/free/en/papers/wen-2023-hard-prompts-made-easy-gradient/) 1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations* 2. [**Universal and Transferable Adversarial Attacks on Aligned Language Models arXiv:2307.15043**Andy Zou, Zifan Wang, Nicholas Carlini, et al.*2023 · 1,005 citations*](https://md.research.elamur.ai/free/en/papers/zou-2023-universal-transferable-adversarial-attacks-aligned/) 3. [**Large Language Models as Optimizers arXiv:2309.03409**Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.*2023 · 413 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-large-language-models-optimizers/) 4. [**HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal arXiv:2402.04249**Mantas Mazeika, Long Phan, Xuwang Yin, et al.*2024 · 330 citations*](https://md.research.elamur.ai/free/en/papers/mazeika-2024-harmbench-standardized-evaluation-framework-automated/) 5. **[Tree of Attacks: Jailbreaking Black-Box LLMs Automatically](https://md.research.elamur.ai/free/en/papers/mehrotra-2023-tree-attacks-jailbreaking-black-box/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, et al.*2023 · 251 citations* 6. [**Baseline Defenses for Adversarial Attacks Against Aligned Language Models arXiv:2309.00614**Neel Jain, Avi Schwarzschild, Yuxin Wen, et al.*2023 · 236 citations*](https://md.research.elamur.ai/free/en/papers/jain-2023-baseline-defenses-adversarial-attacks-against/) 7. [**Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation arXiv:2310.06987**Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-catastrophic-jailbreak-open-source-llms/) 8. [**PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization arXiv:2310.16427**Xinyuan Wang, Chenxi Li, Zhen Wang, et al.*2023 · 102 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-promptagent-strategic-planning-language-models/) 9. **[Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs](https://md.research.elamur.ai/free/en/papers/ong-2024-optimizing-instructions-demonstrations-multi-stage/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, et al.*2024 · 99 citations* 10. [**AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models arXiv:2310.15140**Sicheng Zhu, Ruiyi Zhang, Bang An, et al.*2023 · 90 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-autodan-interpretable-gradient-based-adversarial/) 11. [**In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering arXiv:2311.06668**Sheng Liu, Haotian Ye, Lei Xing, et al.*2023 · 89 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-context-vectors-making-context-learning/) 12. [**Explore, Establish, Exploit: Red Teaming Language Models from Scratch arXiv:2306.09442**Stephen Casper, Jason Lin, Joe Kwon, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/casper-2023-explore-establish-exploit-red-teaming/) 13. [**Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment arXiv:2501.13080**Melissa Kazemi Rad, Huy Nghiem, Andy Luo, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/rad-2025-refining-input-guardrails-enhancing-llm/) 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. **[Prompt-R1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-prompt-r1-collaborative-automatic-prompting/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenjin Liu, Haoran Luo, Xueyuan Lin, et al.*2026 · 3 citations* 16. **[In-Context Representation Hijacking](https://md.research.elamur.ai/free/en/papers/yona-2026-context-representation-hijacking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Itay Yona, Amir Sarid, Michael Karasik, et al.*2026 · 2 citations* 17. **[From Attack Surfaces to Actual Operations: A Survey of Modern LLM Jailbreaks](https://md.research.elamur.ai/free/en/papers/zhou-2026-attack-surfaces-actual-operations-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruikang Zhou, Changsheng Sun, Mark Huasong Meng*2026 · 1 citation* 18. **[SHARP: Self-adaptive Harmful Category-aware Prompt Generation for Black-box Jailbreaking](https://md.research.elamur.ai/free/en/papers/xue-2026-sharp-self-adaptive-harmful-category/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yingjie Xue, Xingyou Xia, Jun Zhang, et al.*2026* 19. **[Silencing the Guardrails: Inference-Time Jailbreaking via Dynamic Contextual Representation Ablation](https://md.research.elamur.ai/free/en/papers/xing-2026-silencing-guardrails-inference-time-jailbreaking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenpeng Xing, Moran Fang, Guangtai Wang, et al.*2026* 20. **[StructBreak: Structural Cognitive Overload-Induced Safety Failures in MLLMs](https://md.research.elamur.ai/free/en/papers/luo-2026-structbreak-structural-cognitive-overload-induced/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yang Luo, Liu Xinran, TianTian Ji, et al.*2026* 61 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wen-2023-hard-prompts-made-easy-gradient/) — Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery