🔗 Who cites «Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models»

56 papers of our library cite it (of the 149,439 whose bibliographies we read) · 17 with a page here, the most cited first · ← back to «Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models»

1. Phi-3 Technical Report: A Highly Capable Language Model Locally on Your PhonearXiv:2404.14219Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.2024 · 1,134 citations
2. MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 320 citations
3. Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 152 citations
4. 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
5. 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
6. 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
7. 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
8. 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
9. 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
10. CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Biao Yi, Tiansheng Huang, Baolei Zhang, et al.2026 · 3 citations
11. 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
12. 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
13. CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious AttacksAnnual Meeting of the Association for Computational Linguistics (ACL)Xu Zhang, Hao Li, Zhichao Lu2026
14. OASIS: Mitigating Harmful Fine-tuning Attacks on LLMs via Orthogonal and Adaptive Safety Alignment StrategyAnnual Meeting of the Association for Computational Linguistics (ACL)Jiayu Tang, Guowei Peng, Qiuhao Xie, et al.2026
15. ReasonRec: A Reasoning-Augmented Multimodal Agent for Unified RecommendationFindings of the Association for Computational LinguisticsYihua Zhang, Mingfu Liang, Jiyan Yang, et al.2026
16. SEA-Guard: Culturally Grounded Multilingual Safeguard for Southeast AsiaFindings of the Association for Computational LinguisticsPanuthep Tasawong, Jian Gang Ngui, Alham Fikri Aji, et al.2026
17. Visual Self-Fulfilling Alignment: Shaping Safety-Oriented Personas via Threat-Related ImagesAnnual Meeting of the Association for Computational Linguistics (ACL)Qishun Yang, Shu Yang, Lijie Hu, et al.2026

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