| 2025 | CVPR | Prof. Robot: Differentiable Robot Rendering Without Static and Self-Collisions. | Quanyuan Ruan, Jiabao Lei, Wenhao Yuan, Yanglin Zhang, Dekun Lu, Guiliang Liu, Kui Jia |
| 2025 | ICLR | A Distributional Approach to Uncertainty-Aware Preference Alignment Using Offline Demonstrations. | Sheng Xu, Bo Yue, Hongyuan Zha, Guiliang Liu |
| 2025 | ICLR | Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning. | Bo Yue, Shufan Wang, Ashish Gaurav, Jian Li, Pascal Poupart, Guiliang Liu |
| 2025 | ICLR | Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers. | Runyi Zhao, Sheng Xu, Bo Yue, Guiliang Liu |
| 2025 | ICML | DexScale: Automating Data Scaling for Sim2Real Generalizable Robot Control. | Guiliang Liu, Yueci Deng, Runyi Zhao, Huayi Zhou, Jian Chen, Jietao Chen, Ruiyan Xu, Yunxin Tai, Kui Jia |
| 2025 | ICML | Provably Efficient Exploration in Inverse Constrained Reinforcement Learning. | Bo Yue, Jian Li, Guiliang Liu |
| 2025 | IROS | GAT-Grasp: Gesture-Driven Affordance Transfer for Task-Aware Robotic Grasping. | Ruixiang Wang, Huayi Zhou, Xinyue Yao, Guiliang Liu, Kui Jia |
| 2024 | ECCV | Modelling Competitive Behaviors in Autonomous Driving Under Generative World Model. | Guanren Qiao, Guorui Quan, Rongxiao Qu, Guiliang Liu |
| 2024 | ICLR | Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning. | Sheng Xu, Guiliang Liu |
| 2024 | ICML | Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation. | Guorui Quan, Zhiqiang Xu, Guiliang Liu |
| 2024 | ICML | Confidence Aware Inverse Constrained Reinforcement Learning. | Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart |
| 2024 | ICML | Robust Inverse Constrained Reinforcement Learning under Model Misspecification. | Sheng Xu, Guiliang Liu |
| 2023 | AISTATS | NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge. | Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart |
| 2023 | ICLR | Learning Soft Constraints From Constrained Expert Demonstrations. | Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart |
| 2023 | ICLR | Benchmarking Constraint Inference in Inverse Reinforcement Learning. | Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart |
| 2022 | ICLR | Learning Object-Oriented Dynamics for Planning from Text. | Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart |
| 2022 | ICLR | Distributional Reinforcement Learning with Monotonic Splines. | Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart |
| 2020 | KDD | Cracking the Black Box: Distilling Deep Sports Analytics. | Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu |
| 2020 | WWW | Extracting Knowledge from Web Text with Monte Carlo Tree Search. | Guiliang Liu, Xu Li, Jiakang Wang, Mingming Sun, Ping Li |
| 2020 | SDM | An Advantage Actor-Critic Algorithm with Confidence Exploration for Open Information Extraction. | Guiliang Liu, Xu Li, Mingming Sun, Ping Li |
| 2018 | IJCAI | Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation. | Guiliang Liu, Oliver Schulte |