Who cites «Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery»
- A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
- Universal and Transferable Adversarial Attacks on Aligned Language ModelsarXiv:2307.15043Andy Zou, Zifan Wang, Nicholas Carlini, et al.2023 · 1,005 citations
- Large Language Models as OptimizersarXiv:2309.03409Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.2023 · 413 citations
- HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust RefusalarXiv:2402.04249Mantas Mazeika, Long Phan, Xuwang Yin, et al.2024 · 330 citations
- Tree of Attacks: Jailbreaking Black-Box LLMs AutomaticallyConference on Neural Information Processing Systems (NeurIPS)Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, et al.2023 · 251 citations
- Baseline Defenses for Adversarial Attacks Against Aligned Language ModelsarXiv:2309.00614Neel Jain, Avi Schwarzschild, Yuxin Wen, et al.2023 · 236 citations
- Catastrophic Jailbreak of Open-source LLMs via Exploiting GenerationarXiv:2310.06987Yangsibo Huang, Samyak Gupta, Mengzhou Xia, et al.2023 · 169 citations
- PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt OptimizationarXiv:2310.16427Xinyuan Wang, Chenxi Li, Zhen Wang, et al.2023 · 102 citations
- Optimizing Instructions and Demonstrations for Multi-Stage Language Model ProgramsConference on Empirical Methods in Natural Language Processing (EMNLP)Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, et al.2024 · 99 citations
- AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language ModelsarXiv:2310.15140Sicheng Zhu, Ruiyi Zhang, Bang An, et al.2023 · 90 citations
- In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space SteeringarXiv:2311.06668Sheng Liu, Haotian Ye, Lei Xing, et al.2023 · 89 citations
- Explore, Establish, Exploit: Red Teaming Language Models from ScratcharXiv:2306.09442Stephen Casper, Jason Lin, Joe Kwon, et al.2023 · 52 citations
- Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and AlignmentarXiv:2501.13080Melissa Kazemi Rad, Huy Nghiem, Andy Luo, et al.2025 · 9 citations
- HiddenGuard: Fine-Grained Safe Generation with Specialized Representation RouterAnnual Meeting of the Association for Computational Linguistics (ACL)Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.2026 · 4 citations
- Prompt-R1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement LearningFindings of the Association for Computational LinguisticsWenjin Liu, Haoran Luo, Xueyuan Lin, et al.2026 · 3 citations
- In-Context Representation HijackingAnnual Meeting of the Association for Computational Linguistics (ACL)Itay Yona, Amir Sarid, Michael Karasik, et al.2026 · 2 citations
- From Attack Surfaces to Actual Operations: A Survey of Modern LLM JailbreaksFindings of the Association for Computational LinguisticsRuikang Zhou, Changsheng Sun, Mark Huasong Meng2026 · 1 citation
- SHARP: Self-adaptive Harmful Category-aware Prompt Generation for Black-box JailbreakingAnnual Meeting of the Association for Computational Linguistics (ACL)Yingjie Xue, Xingyou Xia, Jun Zhang, et al.2026
- Silencing the Guardrails: Inference-Time Jailbreaking via Dynamic Contextual Representation AblationFindings of the Association for Computational LinguisticsWenpeng Xing, Moran Fang, Guangtai Wang, et al.2026
- StructBreak: Structural Cognitive Overload-Induced Safety Failures in MLLMsFindings of the Association for Computational LinguisticsYang Luo, Liu Xinran, TianTian Ji, et al.2026
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