3 papers
cs.CL2025
RuozhiBench: Evaluating LLMs with Logical Fallacies and Misleading Premises
Zenan Zhai, Hao Li, Xudong Han +4
Recent advances in large language models (LLMs) have shown that they can answer questions requiring complex reasoning. However, their ability to identify and respond to text contai…
cs.CL2024
Libra-Leaderboard: Towards Responsible AI through a Balanced Leaderboard of Safety and Capability
Haonan Li, Xudong Han, Zenan Zhai +32
To address this gap, we introduce Libra-Leaderboard, a comprehensive framework designed to rank LLMs through a balanced evaluation of performance and safety. Combining a dynamic le…
cs.CL2024
A Chinese Dataset for Evaluating the Safeguards in Large Language Models
Yuxia Wang, Zenan Zhai, Haonan Li +6
Many studies have demonstrated that large language models (LLMs) can produce harmful responses, exposing users to unexpected risks when LLMs are deployed. Previous studies have pro…