Xianpeng Lang

LinkVLA tackles the language-action misalignment problem in autonomous driving by unifying language and action tokens in a shared space, leading to faster and more accurate instruction following.

MLLMs that ace simple traffic rules still struggle when multiple rules interact, especially when they conflict, revealing a critical gap in their ability to handle real-world driving complexity.