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cs.RO2026
AnyScene: Towards Highly Controllable Driving Scene Generation at Anywhere and Beyond
Haiming Zhang, Junfei Zhou, Feng Jiang +6
Generating high-fidelity and controllable synthetic data is critical for advancing end-to-end autonomous driving, particularly for addressing the long tail of rare safety-critical…
cs.RO2026
MindVLA-U1: VLA Beats VA with Unified Streaming Architecture for Autonomous Driving
Yuzhou Huang, Benjin Zhu, Hengtong Lu +6
Autonomous driving has progressed from modular pipelines toward end-to-end unification, and Vision-Language-Action (VLA) models are a natural extension of this journey beyond Visio…
cs.RO2025
From Words to Safety: Language-Conditioned Safety Filtering for Robot Navigation
Zeyuan Feng, Haimingyue Zhang, Somil Bansal
As robots become increasingly integrated into open-world, human-centered environments, their ability to interpret natural language instructions and adhere to safety constraints is…