3 citations · 8 across the 5 of their papers we have counts for
4 papers · 1 filter
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…
Against The Achilles' Heel: A Survey on Red Teaming for Generative Models
Lizhi Lin, Honglin Mu, Zenan Zhai +9
Generative models are rapidly gaining popularity and being integrated into everyday applications, raising concerns over their safe use as various vulnerabilities are exposed. In li…
Learning From Failure: Integrating Negative Examples when Fine-tuning Large Language Models as Agents
Renxi Wang, Haonan Li, Xudong Han +2
Large language models (LLMs) have achieved success in acting as agents, which interact with environments through tools such as search engines. However, LLMs are optimized for langu…
Can Large Language Model Comprehend Ancient Chinese? A Preliminary Test on ACLUE
Yixuan Zhang, Haonan Li
Large language models (LLMs) have showcased remarkable capabilities in understanding and generating language. However, their ability in comprehending ancient languages, particularl…