10 papers
DriveVLA-M0: Failure-Aware Memory Augmentation for Autonomous Driving
Zebin Xing, Yupeng Zheng, Qiang Chen +10
Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for end-to-end autonomous driving by enabling unified reasoning across perception, language, and p…
U-STS-LLM A Unified Spatio-Temporal Steered Large Language Model for Traffic Prediction and Imputation
Yichen Zhang, Jun Li
The efficient operation of modern cellular networks hinges on the accurate analysis of spatio-temporal traffic data. Mastering these patterns is essential for core network function…
PI-TTA: Physics-Informed Source-Free Test-Time Adaptation for Robust Human Activity Recognition on Mobile Devices
Changyu Li, Lu Wang, Ming Lei +4
Source-free test-time adaptation (TTA) is appealing for mobile and wearable sensing because it enables on-device personalization from unlabeled test streams without centralizing pr…
DreamerAD: Efficient Reinforcement Learning via Latent World Model for Autonomous Driving
Pengxuan Yang, Yupeng Zheng, Deheng Qian +11
We introduce DreamerAD, the first latent world model framework that enables efficient reinforcement learning for autonomous driving by compressing diffusion sampling from 100 steps…
Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Driving
Linbo Wang, Yupeng Zheng, Qiang Chen +13
We introduce Latent-WAM, an efficient end-to-end autonomous driving framework that achieves strong trajectory planning through spatially-aware and dynamics-informed latent world re…
Cheers: Decoupling Patch Details from Semantic Representations Enables Unified Multimodal Comprehension and Generation
Yichen Zhang, Da Peng, Zonghao Guo +19
A recent cutting-edge topic in multimodal modeling is to unify visual comprehension and generation within a single model. However, the two tasks demand mismatched decoding regimes…