Papers with safety training techniques
A Comprehensive Study of Jailbreak Attack versus Defense for Large Language Models (2024.findings-acl)
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| Challenge: | Large Language Models (LLMs) have demonstrated capabilities for generating content that could be deemed harmful. |
| Approach: | They conduct a comprehensive analysis of existing studies on jailbreaking LLMs and their defense techniques. |
| Outcome: | The proposed techniques underperform existing white-box attacks and include special tokens significantly affects the likelihood of successful attacks. |
Can Textual Unlearning Solve Cross-Modality Safety Alignment? (2024.findings-emnlp)
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Trishna Chakraborty, Erfan Shayegani, Zikui Cai, Nael Abu-Ghazaleh, M. Salman Asif, Yue Dong, Amit Roy-Chowdhury, Chengyu Song
| Challenge: | integrating new modalities into large language models creates new attack surface . existing safety training techniques like SFT and RLHF are not feasible in multi-modal settings . |
| Approach: | They explore whether unlearning in the textual domain can be effective for cross-modality safety alignment. |
| Outcome: | The proposed approach reduces the Attack Success Rate (ASR) to less than 8% and preserves the utility. |