4 citations · 4 across the 6 of their papers we have counts for
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cs.CL2026
Hierarchical Alignment: Enforcing Hierarchical Instruction-Following in LLMs through Logical Consistency
Shu Yang, Zihao Zhou, Di Wang +1
Large language models increasingly operate under multiple instructions from heterogeneous sources with different authority levels, including system policies, user requests, tool ou…
cs.CL2024
Uncertainty is Fragile: Manipulating Uncertainty in Large Language Models
Qingcheng Zeng, Mingyu Jin, Qinkai Yu +12
Large Language Models (LLMs) are employed across various high-stakes domains, where the reliability of their outputs is crucial. One commonly used method to assess the reliability…
cs.CL2024★ 4 cited
AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models
Dong Shu, Chong Zhang, Mingyu Jin +3
Jailbreak attacks represent one of the most sophisticated threats to the security of large language models (LLMs). To deal with such risks, we introduce an innovative framework tha…