Papers by Siyuan Deng
FLASH: Focused Layer Attention Sink Hijacking (2026.findings-acl)
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| Challenge: | Large Language Models (LLMs) remain vulnerable to jailbreaking attacks despite advances in safety alignment . |
| Approach: | They propose a new diagnostic auditing framework that dismantles the model's internal safety anchor by precisely scaling attention scores in these vulnerable layers. |
| Outcome: | The proposed framework achieves a state-of-the-art Attack Success Rate of over 77% with an unprecedented efficiency of 1.53 queries on average. |
Editing Large Language Models: Problems, Methods, and Opportunities (2023.emnlp-main)
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Yunzhi Yao, Peng Wang, Bozhong Tian, Siyuan Cheng, Zhoubo Li, Shumin Deng, Huajun Chen, Ningyu Zhang
| Challenge: | Recent advances in model editing for LLMs have created challenges and opportunities for the community. |
| Approach: | They propose to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. |
| Outcome: | The proposed method alters behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. |