3 papers
cs.RO2026
Driver-WM: A Driver-Centric Traffic-Conditioned Latent World Model for In-Cabin Dynamics Rollout
Haozhuang Chi, Daosheng Qiu, Hao Su +4
Safe L2/L3 driving automation requires anticipating human-in-the-loop reactions during shared-control transitions. While most driving world models forecast the external environment…
cs.RO2026
Risk-Aware Selective Multimodal Driver Monitoring with Driver-State World Modeling
Daosheng Qiu, Haozhuang Chi, Hao Su +4
Continuous driver monitoring in automated vehicles requires low-latency inference while avoiding unsafe decisions under uncertain driver states. Large vision-language models provid…
cs.RO2026
Event-Driven Proactive Assistive Manipulation with Grounded Vision-Language Planning
Fengkai Liu, Hao Su, Haozhuang Chi +6
Assistance in collaborative manipulation is often initiated by user instructions, making high-level reasoning request-driven. In fluent human teamwork, however, partners often infe…