Representation Gap in Deep Reinforcement Learning. - Qiang He; Huangyuan Su; Jieyu Zhang; Xinwen Hou (CoRR, 2022)

Reinventing Policy Iteration under Time Inconsistency. - Nixie S. Lesmana; Huangyuan Su; Chi Seng Pun (Trans. Mach. Learn. Res., 2022)

Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning. - Qiang He; Huangyuan Su; Jieyu Zhang 001; Xinwen Hou (CVPR, 2023)

Diffusion-ES: Gradient-Free Planning with Diffusion for Autonomous and Instruction-Guided Driving. - Brian Yang; Huangyuan Su; Nikolaos Gkanatsios; Tsung-Wei Ke; Ayush Jain; Jeff G. Schneider; Katerina Fragkiadaki (CVPR, 2024)

Tractable Joint Prediction and Planning over Discrete Behavior Modes for Urban Driving. - Adam Villaflor; Brian Yang; Huangyuan Su; Katerina Fragkiadaki; John M. Dolan; Jeff G. Schneider (ICRA, 2024)

Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction Following. - Brian Yang; Huangyuan Su; Nikolaos Gkanatsios; Tsung-Wei Ke; Ayush Jain; Jeff Schneider 001; Katerina Fragkiadaki (CoRR, 2024)

Data-Efficient Multi-Agent Spatial Planning with LLMs. - Huangyuan Su; Aaron Walsman; Daniel Garces; Sham M. Kakade; Stephanie Gil (CoRR, 2025)

Interpreting the Linear Structure of Vision-language Model Embedding Spaces. - Isabel Papadimitriou; Huangyuan Su; Thomas Fel; Naomi Saphra; Sham M. Kakade; Stephanie Gil (CoRR, 2025)

Characterization and Mitigation of Training Instabilities in Microscaling Formats. - Huangyuan Su; Mujin Kwun; Stephanie Gil; Sham M. Kakade; Nikhil Anand (CoRR, 2025)