Does LLM Alignment Really Need Diversity? An Empirical Study of Adapting RLVR Methods for Moral Reasoning
Zhaowei Zhang (张钊为)
Ph.D. Student
School of Intelligence Science and Technology
Peking University
Email: zwzhang [at] stu (dot) pku (dot) edu (dot) cn
[Google Scholar] [Github] [Twitter] [LinkedIn]
Research Interests
- Generative AI
- Omni MLLM & World Models
- Efficient AI
- Reinforcement Learning
Zhaowei is pronounced as "Ju" (as in judge) + "ou" (as in out) + "Way"; Zhang, or Cheung in Hong Kong, is "Ju" (as in judge) + "on" | audio ([International Phonetic Alphabet, IPA]) here: [tʂɑuwei][tʂɑŋ].
I am currently a third-year Ph.D. candidate at Institute for AI, School of Intelligence Science and Technology, Peking University. Specifically, I am in the team of PAIR-Lab led by Prof. Yaodong Yang. The long-term goal of my research is to explore the edge of intelligence in the scaling process and how such intelligence can better serve human society. I have previously focused on problems in online convex learning, reinforcement learning, AI alignment, and LLM reasoning. Currently, the question I care most about is how to build a strong and efficient multimodal system that can make the most use of computational resources to achieve the greatest possible scaling. I welcome more friends to discuss these topics with me ☺️.
