🔗 Who cites «JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks»

59 papers of our library cite it (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · ← back to «JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks»

1. NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning ModelarXiv:2508.14444NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.2025 · 39 citations
2. VLSBench: Unveiling Visual Leakage in Multimodal SafetyAnnual Meeting of the Association for Computational Linguistics (ACL)Xuhao Hu, Dongrui Liu, Hao Li, et al.2025 · 32 citations
3. Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic ReasoningarXiv:2512.20848NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.2025 · 27 citations
4. AGrail: A Lifelong Agent Guardrail with Effective and Adaptive Safety DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Weidi Luo, Shenghong Dai, Xiaogeng Liu, et al.2025 · 20 citations
5. Jailbreak Large Vision-Language Models Through Multi-Modal LinkageAnnual Meeting of the Association for Computational Linguistics (ACL)Yu Wang, Xiaofei Zhou, Yichen Wang, et al.2025 · 20 citations
6. Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy DistillationarXiv:2603.19220Zhuolin Yang, Zihan Liu, Yang Chen, et al.2026 · 16 citations
7. HiddenDetect: Detecting Jailbreak Attacks against Multimodal Large Language Models via Monitoring Hidden StatesAnnual Meeting of the Association for Computational Linguistics (ACL)Yilei Jiang, Xinyan Gao, Tianshuo Peng, et al.2025 · 15 citations
8. Rethinking Jailbreak Detection of Large Vision Language Models with Representational Contrastive ScoringAnnual Meeting of the Association for Computational Linguistics (ACL)Peichun Hua, Hao Li, Shanghao Shi, et al.2026 · 10 citations
9. GAMBIT: A Gamified Jailbreak Framework for Multimodal Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiangdong Hu, Yangyang Jiang, Qin Hu, et al.2026 · 6 citations
10. HAUNTATTACK: When Attack Follows Reasoning as a ShadowFindings of the Association for Computational LinguisticsJingyuan Ma, Rui Li, Zheng Li, et al.2026 · 3 citations
11. SafeMT: Multi-turn Safety for Multimodal Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Han Zhu, Juntao Dai, Jiaming Ji, et al.2026 · 3 citations
12. USB: A COMPREHENSIVE AND UNIFIED SAFETY EVALUATION BENCHMARK FOR MULTIMODAL LARGE LANGUAGE MODELSAnnual Meeting of the Association for Computational Linguistics (ACL)Baolin Zheng, Guanlin Chen, Qingyang Teng, et al.2026 · 1 citation
13. When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily LifeFindings of the Association for Computational LinguisticsXinyue Lou, Xu Jinan, Jingyi Yin, et al.2026 · 1 citation
14. CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious AttacksAnnual Meeting of the Association for Computational Linguistics (ACL)Xu Zhang, Hao Li, Zhichao Lu2026
15. Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety AlignmentFindings of the Association for Computational LinguisticsZhixue Song, Boyan Han, Yiwei Wang, et al.2026
16. MLingualFC: Evaluating Jailbreak Vulnerabilities in Multilingual Vision-Language ModelsWorkshop on Multilinguality in the Era of Large Language ModelsRishabh Makwana, Mamta Mamta, Deeksha Varshney, et al.2026
17. PII-VisBench: Evaluating Personally Identifiable Information Safety in Vision Language Models Along a Continuum of VisibilityFindings of the Association for Computational LinguisticsG M Shahariar, Zabir Al Nazi, Md Olid Hasan Bhuiyan, et al.2026
18. SafetyMem: Adaptive Jailbreak Defense via Dual-Component Safety MemoryAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Wang, Ziyi Ni, Huacan Wang, et al.2026
19. StealthGraph: Exposing Domain-Specific Risks in LLMs through Knowledge-Graph-Guided Harmful Prompt GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Huawei Zheng, Xinqi Jiang, Sen Yang, et al.2026

40 more papers of our library cite it; they have no page here yet.

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