Learning Control Admissibility Models with Graph Neural Networks for Multi-Agent Navigation. - Chenning Yu; Hongzhan Yu; Sicun Gao (CoRL, 2022)

Sequential Neural Barriers for Scalable Dynamic Obstacle Avoidance. - Hongzhan Yu; Chiaki Hirayama; Chenning Yu; Sylvia L. Herbert; Sicun Gao (IROS, 2023)

Activation-Descent Regularization for Input Optimization of ReLU Networks. - Hongzhan Yu; Sicun Gao (ICML, 2024)

ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning. - Christopher E. Mower; Yuhui Wan; Hongzhan Yu; Antoine Grosnit; Jonas Gonzalez-Billandon; Matthieu Zimmer; Jinlong Wang; Xinyu Zhang; Yao Zhao; Anbang Zhai; Puze Liu; Davide Tateo; et al. (CoRR, 2024)

Controllable Motion Generation via Diffusion Modal Coupling. - Luobin Wang; Hongzhan Yu; Chenning Yu; Sicun Gao; Henrik I. Christensen (CoRR, 2025)

Estimating Control Barriers from Offline Data. - Hongzhan Yu; Seth Farrell; Ryo Yoshimitsu; Zhizhen Qin; Henrik I. Christensen; Sicun Gao (CoRR, 2025)

Safe Human Robot Navigation in Warehouse Scenario. - Seth Farrell; Chenghao Li; Hongzhan Yu; Ryo Yoshimitsu; Sicun Gao; Henrik I. Christensen (CoRR, 2025)

Sequence Modeling for Time-Optimal Quadrotor Trajectory Optimization with Sampling-based Robustness Analysis. - Katherine Mao; Hongzhan Yu; Ruipeng Zhang; Igor Spasojevic; M. Ani Hsieh; Sicun Gao; Vijay Kumar 001 (CoRR, 2025)