Papers by Yutong Ke
“I’ve Decided to Leak”: Probing Internals Behind Prompt Leakage Intents (2025.emnlp-main)
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Jianshuo Dong, Yutong Zhang, Liu Yan, Zhenyu Zhong, Tao Wei, Ke Xu, Minlie Huang, Chao Zhang, Han Qiu
| Challenge: | Large language models (LLMs) exhibit prompt leakage vulnerabilities, raising intellectual property and confidentiality concerns. |
| Approach: | They use probing techniques to capture LLMs’ intent-related internal representations and show that they internalize prompt leakage intents in their hidden states before generating tokens. |
| Outcome: | The proposed probes achieve 90%+ AUROC across all tested models, even when applied to new system prompts and attacks. |
Unraveling LLM Jailbreaks Through Safety Knowledge Neurons (2026.eacl-long)
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| Challenge: | Large Language Models (LLMs) have achieved significant progress in alignment, ensuring safer and more reliable outputs. |
| Approach: | They propose a neuron-level interpretability method that focuses on the role of safety-related knowledge neurons to improve model robustness against jailbreak attacks. |
| Outcome: | The proposed method reduces attack success rates across multiple LLMs and outperforms all baseline defenses. |