About me

I am a CS PhD student at UIUC, advised by Prof. Tong Zhang and Prof. Huan Zhang. Previously, I earned my bachelor’s and master’s degrees from the Department of Automation at Tsinghua University and CSE, HKUST. Currently, my research focuses on: Agents, Trustworthy LLMs/VLMs, and Deep reinforcement learning.

Prior to my PhD, I am fortunate to have been working closely with Prof. Chongjie Zhang (Washington University in St. Louis), Dr. Lei Han (Tencent AI Lab), and Prof. Meng Fang (University of Liverpool).

News

• 🌟 (2025.6) We’ve released GUI-Actor, a novel GUI grounding model that combines an attention-based action head with a grounding verifier. Explore more on our project page!
• 💻 (2025.5) Starting my internship at Microsoft Research, Redmond.
• 🎉 (2025.5) Decomposed Reward Models (DRMs) is accepted to ACL 2025.
• 🎉 (2025.5) EmbodiedBench is accepted to ICML 2025 as an oral paper! Thanks to my co-authors!
• 🌟 (2025.02) We released EmbodiedBench, a new comprehensive and multifaceted benchmark for multimodal embodied agents. Check out our paper and project page.
• 🎉 (2025.1) Robust Decision Transformer and DynaMath are accepted by ICLR 2025! New versions will be updated soon.
• 🌟 (2024.10) A dynamic visual math benchmark is out! Check the project page and the DynaMath paper.
• 🎉 (2024.9) GRM is accepted by NeurIPS 2024! Check out our GRM series here.
• 🎉 (2024.5) Rewards-in-Context (RiC) is accepted by ICML 2024! Thanks to my co-authors!
• 🎉 (2024.1) Robust IQL is accepted by ICLR 2024 as a spotlight paper!

Selected Publications

Multimodal GUI Agent

• GUI-Actor: Attention-based Grounding with Verifiable Action Head for GUI Agents. Preprint 2025. [code] [website] Qianhui Wu$^*$, Kanzhi Cheng$^*$, Rui Yang$^*$, Chaoyun Zhang, Jianwei Yang, Huiqiang Jiang, Jian Mu, Baolin Peng, Bo Qiao, Reuben Tan, Si Qin, Lars Liden, Qingwei Lin, Huan Zhang, Tong Zhang, Jianbing Zhang, Dongmei Zhang, Jianfeng Gao

Multimodal Embodied Agent

• EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents. ICML 2025 (Oral). [code] [website]
  Rui Yang$^*$, Hanyang Chen $^*$, Junyu Zhang $^*$, Mark Zhao $^*$, Cheng Qian, Kangrui Wang, Qineng Wang, Teja Venkat Koripella, Marziyeh Movahedi, Manling Li, Heng Ji, Huan Zhang, Tong Zhang

Multimodal Math Reasoning

• DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models. ICLR 2025. [code] [website]
  Chengke Zou $^*$, Xingang Guo $^*$, Rui Yang $^*$, Junyu Zhang, Bin Hu, Huan Zhang.

ML for LLMs

• Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs. NeurIPS 2024. [code]
  Rui Yang, Ruomeng Ding, Yong Lin, Huan Zhang, Tong Zhang.

• Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment. ICML 2024. [code]
  Rui Yang $^*$, Xiaoman Pan $^*$, Feng Luo $^*$, Shuang Qiu $^*$, Han Zhong, Dong Yu, Jianshu Chen.

Robust Offline RL

• Robust Decision Transformer: Tackling Data Corruption in Offline RL via Sequence Modeling. ICLR 2025.
  Jiawei Xu $^*$, Rui Yang $^*$, Shuang Qiu, Feng Luo, Meng Fang, Baoxiang Wang, Lei Han.

• Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. ICLR 2024. (Spotlight) [code]
  Rui Yang $^*$, Han Zhong $^*$, Jiawei Xu $^*$, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang.

• Corruption-Robust Offline Reinforcement Learning with General Function Approximation. NeurIPS 2023. [code]
  Chenlu Ye $^*$, Rui Yang $^*$, Quanquan Gu, Tong Zhang.

• RORL: Robust Offline Reinforcement Learning via Conservative Smoothing. NeurIPS 2022. (Spotlight) [code]
  Rui Yang $^*$, Chenjia Bai $^*$, Xiaoteng Ma, Zhaoran Wang, Chongjie Zhang, Lei Han.

Goal-conditioned RL

• What Is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL?. ICML 2023. [code]
  Rui Yang, Yong Lin, Xiaoteng Ma, Hao Hu, Chongjie Zhang, Tong Zhang.

• Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL. ICLR 2022. [code]
  Rui Yang, Yiming Lu, Wenzhe Li, Hao Sun, Meng Fang, Yali Du, Xiu Li, Lei Han, Chongjie Zhang.

• GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models. TMLR 2024.
  Mianchu Wang $^*$, Rui Yang $^*$, Xi Chen, Hao Sun, Meng Fang, Giovanni Montana.

Experiences

• Research Intern at Microsoft Research, 2025.

• Research Intern at Tencent AI Lab and Robotics X Lab, 2020-2022 (Multiple internship terms).

• ML Intern at Meituan Financial Service Group, 2019.

Services

Conference Reviewer: ICML, ICLR, NeurIPS ($\color{red}{\text{Top Reviewer}}$ in NeurIPS 2023), ACL/ARR, ICRA, AAMAS.

Journal Reviewer: IEEE Robotics and Automation Letters (RA-L), IEEE Transactions on Artificial Intelligence (TAI), Machine Learning, Journal of Artificial Intelligence Research.

Teaching Assistant: COMP 4211 Machine Learning, HKUST; COMP 1021 Introduction to Computer Science, HKUST

Hobbies

In my leisure time, I enjoy sports like running, table tennis, and swimming. During my time at Tsinghua University, I was an amateur long-distance runner. In 2019, I completed a half marathon (21.0975 km) in 1 h 30 m and a full marathon (42.195 km) in 3 h 36 m.