4 papers · 1 filter
Look Before Acting: Enhancing Vision Foundation Representations for Vision-Language-Action Models
Yulin Luo, Hao Chen, Zhuangzhe Wu +10
Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for robotic manipulation, in which reliable action prediction critically depends on accurately int…
World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model
Yupeng Zheng, Pengxuan Yang, Zebin Xing +8
End-to-end autonomous driving directly generates planning trajectories from raw sensor data, yet it typically relies on costly perception supervision to extract scene information.…
DriveAction: A Benchmark for Exploring Human-like Driving Decisions in VLA Models
Yuhan Hao, Zhengning Li, Lei Sun +7
Vision-Language-Action (VLA) models have advanced autonomous driving, but existing benchmarks still lack scenario diversity, reliable action-level annotation, and evaluation protoc…
TokenFLEX: Unified VLM Training for Flexible Visual Tokens Inference
Junshan Hu, Jialiang Mao, Zhikang Liu +3
Conventional Vision-Language Models(VLMs) typically utilize a fixed number of vision tokens, regardless of task complexity. This one-size-fits-all strategy introduces notable ineff…