Lirui Luo

PKU & JD TGT, Beijing, China

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I am a Ph.D. student in the School of Intelligence at Peking University (PKU), majoring in Computer Science and Technology (Intelligent Science and Technology), advised by Cong Fang. I received my B.E. in Communication Engineering from the School of Electronic and Information Engineering at Beijing Jiaotong University (BJTU) in 2023.

I am currently an intern at JD.com’s Tech Genius Team (TGT, Top Young Technical Talent Program), working on Agentic RL post-training for e-commerce agents.

My research focuses on continual reinforcement learning for agents that learn, adapt, and self-improve through long-term interaction. I study how reinforcement learning agents preserve plasticity, acquire new skills, and evolve across changing tasks and environments. Recently, I have also been exploring continual reinforcement learning for large models, including RLVR-style training, agent self-improvement, and post-training for practical agentic systems.

news

Jun 24, 2026 Joined JD.com’s Tech Genius Team (TGT, Top Young Technical Talent Program) as an intern, working on Agentic RL post-training for e-commerce agents.
May 05, 2026 SPHERE accepted by ICML 2026.
Jan 30, 2026 MVR accepted by ICLR 2026.
Jun 13, 2024 INSIGHT has been selected as a spotlight-designated paper.
May 22, 2024 INSIGHT accepted by ICML 2024.

experiences

publications

  1. ICML
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    SPHERE: Mitigating the Loss of Spectral Plasticity in Mixture-of-Experts for Deep Reinforcement Learning
    Lirui Luo, Guoxi Zhang, Hongming Xu, and 2 more authors
    In Proceedings of the 43rd International Conference on Machine Learning , 2026
  2. ICLR
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    MVR: Multi-view Video Reward Shaping for Reinforcement Learning
    Lirui Luo, Guoxi Zhang, Hongming Xu, and 3 more authors
    ICLR, 2026
  3. ICML
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    End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations
    Lirui Luo, Guoxi Zhang, Hongming Xu, and 3 more authors
    ICML, 2024