Luo, W., Ma, S., Liu, X., Guo, X., & Xiao, C. (2024). JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks. https://arxiv.org/abs/2404.03027 JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak AttacksWith the rapid advancements in Multimodal Large Language Models (MLLMs), securing..

Shen, X., Chen, Z., Backes, M., Shen, Y., & Zhang, Y. (2023). " do anything now": Characterizing and evaluating in-the-wild jailbreak prompts on large language models. arXiv preprint arXiv:2308.03825.https://arxiv.org/abs/2308.03825 "Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language ModelsThe misuse of large language models (LLMs) has drawn significa..

Direct Preference Optimization: Your Language Model is Secretly a Reward Model, Advances in Neural Information Processing Systems (Neurips,'24). Rafailov, R., Sharma, A., Mitchell, E., Manning, C. D., Ermon, S., & Finn, C.https://arxiv.org/abs/2305.18290 Direct Preference Optimization: Your Language Model is Secretly a Reward ModelWhile large-scale unsupervised language models (LMs) learn broad ..