5 papers
ASSCG: Just-Right Gating over Chattering for Fast-Slow LLM Planning in Autonomous Driving
Sining Ang, Yuan Chen, Liu Haiyan +5
Large language models (LLMs) can improve autonomous driving planning but are costly to query online, and existing fast-slow planners often rely on hand-designed triggering rules th…
AR Forcing: Towards Long-Horizon Robot Navigation World Model
Yifei Yang, Zehua Fan, Huan Li +9
The diffusion based robot navigation world models are typically trained using parallel supervision, while autoregressive inference is employed during path planning. This results in…
Devil is in Narrow Policy: Unleashing Exploration in Driving VLA Models
Canyu Chen, Yuguang Yang, Zhewen Tan +10
We identify a fundamental Narrow Policy limitation undermining the performance of autonomous VLA models, where driving Imitation Learning (IL) tends to collapse exploration and lim…
PROSPECT: Unified Streaming Vision-Language Navigation via Semantic--Spatial Fusion and Latent Predictive Representation
Zehua Fan, Wenqi Lyu, Wenxuan Song +12
Multimodal large language models (MLLMs) have advanced zero-shot end-to-end Vision-Language Navigation (VLN), yet robust navigation requires not only semantic understanding but als…
SparseWorld: A Flexible, Adaptive, and Efficient 4D Occupancy World Model Powered by Sparse and Dynamic Queries
Chenxu Dang, Haiyan Liu, Jason Bao +6
Semantic occupancy has emerged as a powerful representation in world models for its ability to capture rich spatial semantics. However, most existing occupancy world models rely on…