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Changxun Pan

Yao Class, Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University

Research Interests

Vision-Language-Action Models, Robot Learning, Memory for Embodied Agents, Multimodal Learning

Education

Tsinghua University, Beijing
B.Eng. in Computer Science and Technology, Yao Class, IIIS
Sept. 2024 — Jul. 2028 (expected)

Research Experience

Galaxea AI — Research Intern
Advisor: Prof. Hang Zhao
Jan. 2026 — Present
  • Contributed to large-scale object-centric and geometric supervision for G0.5 robot pretraining data.
  • Built a two-stage bounding-box pipeline using language-model prompting for task-relevant keyframes and SAM 3 for temporal propagation.
  • Parallelized language-model inference across workers and mask propagation across multiple GPUs for efficient scaling.
  • Investigated multimodal point-prediction and tracking approaches for 2D motion traces, then developed a faster URDF-based solution.
  • Generated three-view 2D trajectories of dual-arm gripper/end-effector points for R1 Lite and R1 Pro using kinematic projection and GPU acceleration.
  • The pipelines were applied to nearly 10,000 hours of robot data for pretraining; directly validated quality and reliability on several hundred hours.
Memory-Augmented VLA Models for Long-Horizon Manipulation
2026 — Present
  • Exploring recurrent mid-layer latent memory, where adapted hidden representations are carried forward as memory tokens for the next policy inference.
  • Investigating a memory-bank training scheme that supports random sampling while avoiding full BPTT across long episodes.
  • Current experiments use G0.5 as the backbone and memory-oriented benchmarks including RMBench, MIKASA, and RoboMME.

Preprint

G0.5: One Autoregressive Stream for Robot Reasoning and Action
Yicheng Liu, Zibin Dong, Baijun Ye, …, Changxun Pan, …, Hang Zhao
arXiv preprint, 2026

Honors & Awards

Chinese Physics Olympiad — National Gold Medal, ranked 25th nationally2023
National Encouragement Scholarship2025
Tsinghua University Comprehensive Excellence Scholarship2025

Selected Coursework & Skills

Coursework: Machine Learning, Natural Language Processing, Computer Vision, Advanced Computer Graphics, Large Language Model Applications, Multimodal Machine Learning

Programming: Python, C++  ·  ML: PyTorch  ·  Tools: Git, Linux