1 citations · 1 across the 4 of their papers we have counts for
4 papers
Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm
Zhuo Li, Yuhao Du, Xiaoqi Jiao +5
Selecting high-quality and diverse training samples from extensive datasets plays a crucial role in reducing training overhead and enhancing the performance of Large Language Model…
RLHF in an SFT Way: From Optimal Solution to Reward-Weighted Alignment
Yuhao Du, Zhuo Li, Pengyu Cheng +4
Reinforcement Learning from Human Feedback (RLHF) is crucial for aligning Large Language Models (LLMs) with human values. However, RLHF has been continuously challenged by its high…
Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs
Zhuo Li, Yuhao Du, Jinpeng Hu +2
Large language models (LLMs) have shown success in generating high-quality responses. In order to achieve better alignment with LLMs with human preference, various works are propos…
Atoxia: Red-teaming Large Language Models with Target Toxic Answers
Yuhao Du, Zhuo Li, Pengyu Cheng +2
Despite the substantial advancements in artificial intelligence, large language models (LLMs) remain being challenged by generation safety. With adversarial jailbreaking prompts, o…