Yiqing Xu

National University of Singapore. yiqing[dot]xu[at]u[dot]nus[dot]edu

prof_pic.jpg

NUS School of Computing, COM1, 13, Computing Dr

Singapore 117417

I’m Yiqing Xu, a CS Ph.D. candidate at the National University of Singapore, advised by Prof. David Hsu. Previously, I obtained double degrees in Computer Science and Applied Mathematics from NUS.

I was a visiting Ph.D. student at MIT CSAIL, advised by Prof. Leslie Kaelbling and Prof. Tomás Lozano-Pérez from September 2023 to February 2024.

research highlights

My research focuses on translating human objectives into signals for robotic optimization. I develop compositional and hierachical structures as intermediate representations and design reward learning algorithms to better align robotic agents with human goals, especially when expert data is scarce or under-specified.

In my latest works, “Set It Up” (IJRR) and “Stack It Up” (CoRL), I explore how robots can act on human goals conveyed through ambiguous but intuitive inputs — like language commands or freehand sketches. Both works share a neuro-symbolic architecture that maps these inputs into abstract relation graphs, then grounds them into feasible physical configurations via compositional diffusion models. This approach preserves task structure, supports generalization, and learns from surprisingly few demonstrations by reusing local relational priors.

I’m excited to extend this framework in two directions. First, toward flexible skill chaining from mixed-modality input — combining coarse, abstract instructions with precise but partial demonstrations to infer symbolic task skeletons and modular reward functions that can be composed and optimized jointly. Second, toward interactive multi-modal goal specification, where robots engage with users via language, gaze, and motion to resolve ambiguity through active dialogue and inference. Across both directions, the goal remains the same: to make goal specification more expressive, adaptable, and aligned with how humans actually communicate intent.

If you’d like to chat more, feel free to email me!

selected publications

  1. RHIRL.png
    Receding Horizon Inverse Reinforcement Learning
    Yiqing Xu, Wei Gao, and David Hsu
    In Advances in Neural Information Processing Systems (NeurIPS), 2022
    arXiv
  2. LLMReward.png
    Learning Reward for Physical Skills using Large Language Model
    Yuwei Zeng, and Yiqing Xu
    In Conference on Robot Learning (CoRL), LangRob workshop, 2023
    arXiv
  3. TidyItUp.png
    "Tidy Up the Table": Grounding Common-sense Objective for Tabletop Object Rearrangement
    Yiqing Xu, and David Hsu
    In Robotics: Science and Systems (RSS), LangRob workshop, 2023
    arXiv
  4. Effective_IRL.png
    On the Effective Horizon of Inverse Reinforcement Learning
    Yiqing Xu, Finale Doshi-Velez, and David Hsu
    In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2025
    arXiv
  5. SetItUp.png
    "Set It Up!": Functional Object Arrangement with Compositional Generative Models (Conference Version)
    Yiqing Xu, Jiayuan Mao, Yilun Du, and 3 more authors
    In Robotics: Science and Systems (RSS), 2024
    arXiv
  6. setitup_ijrr.png
    “Set It Up": Functional Object Arrangement with Compositional Generative Models (Journal Version)
    Yiqing Xu, Jiayuan Mao, Linfeng Li, and 4 more authors
    The International Journal of Robotics Research (IJRR), 2025
    arXiv
  7. stackitup.png
    “Stack It Up!": 3D Stable Structure Generation from 2D Hand-drawn Sketch
    Yiqing Xu, Linfeng Li, Cunjun Yu, and 1 more author
    In Proceedings of the Conference on Robot Learning (CoRL), 2025
    arXiv