1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CR2025★ 1 cited
ForgeDAN: An Evolutionary Framework for Jailbreaking Aligned Large Language Models
Siyang Cheng, Gaotian Liu, Rui Mei +7
The rapid adoption of large language models (LLMs) has brought both transformative applications and new security risks, including jailbreak attacks that bypass alignment safeguards…
cs.AI2025
Synthetic Data-Driven Prompt Tuning for Financial QA over Tables and Documents
Yaoning Yu, Kai-Min Chang, Ye Yu +3
Financial documents like earning reports or balance sheets often involve long tables and multi-page reports. Large language models have become a new tool to help numerical reasonin…
cs.CL2025
SIPDO: Closed-Loop Prompt Optimization via Synthetic Data Feedback
Yaoning Yu, Ye Yu, Peiyan Zhang +3
Prompt quality plays a critical role in the performance of large language models (LLMs), motivating a growing body of work on prompt optimization. Most existing methods optimize pr…