👋 About Me

Hi! I am a second-year master’s student at Tsinghua Shenzhen International Graduate School, Tsinghua University, under the supervision of Prof. Xiu Li. I received my bachelor’s degree with honors from Shandong University in June 2023.

I am fortunate to have collaborated with many great researchers who have generously shared their guidance and insights. Currently, I am a research intern at Large Language Model Center, Shanghai AI Laboratory, advised by Dr. Biqing Qi. Previously, I interned at Intelligent Photonics and Electronics Center (IPEC), Shanghai AI Laboratory, advised by Dr. Chenjia Bai. Before that, I was a research intern at Institute for AI, Peking University, advised by Prof. Yali Du and Prof. Yaodong Yang.

Research Interests: My research focuses on Large Language Models (LLMs) and Reinforcement Learning (RL). I am currently interested in improving the reasoning and generalization capabilities of LLMs and exploring the potential of integrating LLMs to enhance RL algorithms, especially in the context of Reinforcement Learning from Human/AI Feedback (RLHF/RLAIF).

Please feel free to drop me an e-mail if you are interested in collaborating with me.

🔥 News

• [2024.05]  🎉 One paper accepted by ICML 2024
• [2024.01]  🎉 One paper accepted by ICLR 2024
• [2023.10]  🎉 One paper accepted by OTML workshop at NeurIPS 2023
• [2022.09]  🎉 One paper accepted by NeurIPS 2022

📝 Publications

(* indicates equal contribution)

Preprints

• VLP: Vision-Language Preference Learning for Embodied Manipulation
  Runze Liu, Chenjia Bai, Jiafei Lyu, Shengjie Sun, Yali Du, Xiu Li
  In progress

• A Large Language Model-Driven Reward Design Framework via Dynamic Feedback for Reinforcement Learning
  Shengjie Sun*, Runze Liu*, Jiafei Lyu, Jing-Wen Yang, Liangpeng Zhang, Xiu Li
  Preprint, 2024

Conference Papers

• PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation
  Runze Liu, Yali Du, Fengshuo Bai, Jiafei Lyu, Xiu Li
  International Conference on Machine Learning (ICML), 2024

• Meta-Reward-Net: Implicitly Differentiable Reward Learning for Preference-based Reinforcement Learning
  Runze Liu, Fengshuo Bai, Yali Du, Yaodong Yang
  Advances in Neural Information Processing Systems (NeurIPS), 2022

• SEABO: A Simple Search-Based Method for Offline Imitation Learning
  Jiafei Lyu, Xiaoteng Ma, Le Wan, Runze Liu, Xiu Li, Zongqing Lu
  International Conference on Learning Representations (ICLR), 2024

Workshop Papers

• Zero-shot Cross-task Preference Alignment for Offline RL via Optimal Transport
  Runze Liu, Yali Du, Fengshuo Bai, Jiafei Lyu, Xiu Li
  NeurIPS Workshop Optimal Transport and Machine Learning (OTML), 2023

🎓 Education

• Tsinghua University, 2023.09 - 2026.06
  Master’s student in Electronic and Information Engineering (AI)
• Shandong University, 2019.09 - 2023.06
  B.S. in Statistics (Data Science & AI) with honors

🎖 Honors and Awards

• National Scholarship (Top 1%), 2022.12
• National Scholarship (Top 1%), 2021.12
• First Prize in China Undergraduate Mathematical Contest in Modeling (CUMCM) (Top 0.65%), 2021.11
• Outstanding Student of Shandong Province (Top 0.6%), 2022.05
• Outstanding Graduate of Shandong Province (Top 6%), 2023.04
• Dishang Scholarship, 2022.10

💻 Internships

• Research Intern, Large Language Model Center, Shanghai AI Laboratory, 2024.10 - Present.
• Research Intern, Intelligent Photonics and Electronics Center (IPEC), Shanghai AI Laboratory, 2023.07 - 2024.09.
• Research Intern, Institute for AI, Peking University, 2022.01 - 2022.09.

🛠️ Services

• Conference Reviewer: NeurIPS (2024), ICLR (2025), AAMAS (2024), AISTATS (2025), ECAI (2024)
• Workshop Reviewer: NeurIPS OTML (2023)