4 papers · 1 filter
SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture
Haiwen Diao, Penghao Wu, Hanming Deng +55
Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fra…
DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving
Lingjun Zhang, Changjie Wu, Linzhe Shi +6
End-to-end autonomous driving systems are increasingly integrating Vision-Language Model (VLM) architectures, incorporating text reasoning or visual reasoning to enhance the robust…
DriveFuture: Future-Aware Latent World Models for Autonomous Driving
Yufeng Hong, Xiaotian Zhou, Yingyan Li +6
Existing latent world models for autonomous driving have opened a promising path toward future-aware driving intelligence. However, they typically treat future latent states as pre…
Stable at Any Speed: Speed-Driven Multi-Object Tracking with Learnable Kalman Filtering
Yan Gong, Mengjun Chen, Hao Liu +5
Multi-object tracking (MOT) enables autonomous vehicles to continuously perceive dynamic objects, supplying essential temporal cues for prediction, behavior understanding, and safe…