1 citations · 1 across the 5 of their papers we have counts for
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Controllable and Photorealistic Pedestrian Risky Motion Generation for End-to-End Driving Safety Evaluation
Siyuan Liu, Miao Li, Haibao Yu +4
Evaluating end-to-end autonomous driving under rare, safety-critical vehicle-pedestrian interactions requires photorealistic, sensor-level scenarios. However, trajectory-based scen…
Simple Agentic Memory for Generalist Robot Policies
Yuyou Zhang, Yunbei Zhang, Miao Li +4
Visual-memory systems commonly retain or compress past observations. Robot control additionally requires interaction-derived state that no individual frame may explicitly represent…
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…
Privacy Risks in Reinforcement Learning for Household Robots
Miao Li, Wenhao Ding, Ding Zhao
The prominence of embodied Artificial Intelligence (AI), which empowers robots to navigate, perceive, and engage within virtual environments, has attracted significant attention, o…