5 papers
Model-Based Policy Adaptation for Closed-Loop End-to-End Autonomous Driving
Haohong Lin, Yunzhi Zhang, Wenhao Ding +2
End-to-end (E2E) autonomous driving models have demonstrated strong performance in open-loop evaluations but often suffer from cascading errors and poor generalization in closed-lo…
Query-Centric Diffusion Policy for Generalizable Robotic Assembly
Ziyi Xu, Haohong Lin, Shiqi Liu +1
The robotic assembly task poses a key challenge in building generalist robots due to the intrinsic complexity of part interactions and the sensitivity to noise perturbations in con…
Causal Composition Diffusion Model for Closed-loop Traffic Generation
Haohong Lin, Xin Huang, Tung Phan-Minh +6
Simulation is critical for safety evaluation in autonomous driving, particularly in capturing complex interactive behaviors. However, generating realistic and controllable traffic…
CrashAgent: Crash Scenario Generation via Multi-modal Reasoning
Miao Li, Wenhao Ding, Haohong Lin +4
Training and evaluating autonomous driving algorithms requires a diverse range of scenarios. However, most available datasets predominantly consist of normal driving behaviors demo…
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning
Haohong Lin, Wenhao Ding, Jian Chen +4
Offline model-based reinforcement learning (MBRL) enhances data efficiency by utilizing pre-collected datasets to learn models and policies, especially in scenarios where explorati…