4 papers
Multi-Value Alignment for LLMs via Value Decorrelation and Extrapolation
Hefei Xu, Le Wu, Chen Cheng +1
With the rapid advancement of large language models (LLMs), aligning them with human values for safety and ethics has become a critical challenge. This problem is especially challe…
Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions
Kun Zhang, Le Wu, Kui Yu +2
Large Language Models (LLMs) have gained enormous attention in recent years due to their capability of understanding and generating natural languages. With the rapid development an…
R.R.: Unveiling LLM Training Privacy through Recollection and Ranking
Wenlong Meng, Zhenyuan Guo, Lenan Wu +5
Large Language Models (LLMs) pose significant privacy risks, potentially leaking training data due to implicit memorization. Existing privacy attacks primarily focus on membership…
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
Dacao Zhang, Kun Zhang, Shimao Chu +3
With the rapid development of Large Language Models (LLMs), Parameter-Efficient Fine-Tuning (PEFT) methods have gained significant attention, which aims to achieve efficient fine-t…