🔗 Who cites «VLSBench: Unveiling Visual Leakage in Multimodal Safety»

28 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · ← back to «VLSBench: Unveiling Visual Leakage in Multimodal Safety»

1. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and BeyondarXiv:2503.21614Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.2025 · 55 citations
2. Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety AlignmentConference on Empirical Methods in Natural Language Processing (EMNLP)Hao Li, Lijun Li, Zhenghao Lu, et al.2025 · 11 citations
3. Visual Contextual Attack: Jailbreaking MLLMs with Image-Driven Context InjectionConference on Empirical Methods in Natural Language Processing (EMNLP)Miao Ziqi, Yi Ding, Lijun Li, et al.2025 · 6 citations
4. LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-DisjointAnnual Meeting of the Association for Computational Linguistics (ACL)Qianli Ma, Dongrui Liu, Qian Chen, et al.2025 · 5 citations
5. 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
6. 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
7. Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and BenchmarksFindings of the Association for Computational LinguisticsNobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu, et al.2026

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

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